US20010000216A1 - Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms - Google Patents
Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms Download PDFInfo
- Publication number
- US20010000216A1 US20010000216A1 US09/730,330 US73033000A US2001000216A1 US 20010000216 A1 US20010000216 A1 US 20010000216A1 US 73033000 A US73033000 A US 73033000A US 2001000216 A1 US2001000216 A1 US 2001000216A1
- Authority
- US
- United States
- Prior art keywords
- signal
- segments
- analog
- signal segments
- bandwidth
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- H—ELECTRICITY
- H03—ELECTRONIC CIRCUITRY
- H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
- H03M1/00—Analogue/digital conversion; Digital/analogue conversion
- H03M1/12—Analogue/digital converters
- H03M1/1205—Multiplexed conversion systems
- H03M1/121—Interleaved, i.e. using multiple converters or converter parts for one channel
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S1/00—Beacons or beacon systems transmitting signals having a characteristic or characteristics capable of being detected by non-directional receivers and defining directions, positions, or position lines fixed relatively to the beacon transmitters; Receivers co-operating therewith
- G01S1/02—Beacons or beacon systems transmitting signals having a characteristic or characteristics capable of being detected by non-directional receivers and defining directions, positions, or position lines fixed relatively to the beacon transmitters; Receivers co-operating therewith using radio waves
- G01S1/04—Details
- G01S1/045—Receivers
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/021—Auxiliary means for detecting or identifying radar signals or the like, e.g. radar jamming signals
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/28—Details of pulse systems
- G01S7/285—Receivers
Definitions
- the present invention relates generally to a method and apparatus for acquiring wide-band random and pseudorandom noise encoded waveforms and specifically to a method and apparatus for acquiring wide-band signals, including deterministic signals, random signals and pseudorandom noise encoded waveforms that divides the waveform into a plurality of subbands prior to signal processing thereof.
- Analog-to-digital converters are devices that convert real world analog signals into a digital representation or code which a computer can thereafter analyze and manipulate.
- Analog signals represent information by means of continuously variable physical quantities while digital signals represent information by means of differing discrete physical property states.
- Converters divide the full range of the analog signal into a finite number of levels, called quantization levels, and assigns to each level a digital code.
- the total number of quantization levels used by the converter is an indication of its fidelity and is measured in terms of bits. For example, an 8-bit converter uses 2 8 or 256 levels, while a 16-bit converter uses 2 16 or 65536 levels.
- the converter determines the quantization level that is closest to the amplitude of the analog signal at that time and outputs the digital code that represents the selected quantization level.
- the rate at which the output is created indicates the speed of the converter and is measured in terms of samples per second (sps) or frequency in Hertz (Hz). As will be appreciated, a larger number of bits and therefore quantization levels equates into a finer representation of the analog signal.
- the present invention is directed to a method and apparatus for processing signals, particularly wide-band signals, including deterministic signals, random signals, and signals defined by pseudorandom waveforms with a relatively high degree of fidelity and efficiency at a high speed and at a low cost.
- the invention is particularly useful for processing wideband signal, including signals defined by broadband signals (i.e., signals having a bandwidth of preferably more than about 1 kHz and more preferably more than about 1 GHz).
- the signal can be in any suitable form such as electromagnetic radiation, acoustic, electrical and optical.
- the method includes the following steps:
- the means for processing the signal segments can include any number of operations, including filtering, analog-to-digital or digital-to-analog conversion, signal modulation and/or demodulation, object tracking, RAKE processing, beamforming, null steering, correlation, interference-suppression and matched subspace filtering.
- the signal processing step (b) includes either analog-to-digital or digital-to-analog conversions.
- the use of signal segments rather than the entire signal for such conversions permits the use of a lower sampling rate to retain substantially all of the information present in the source signal.
- the sampling frequency of the source signal should be at least twice the bandwidth of the source signal to maintain a high fidelity.
- the ability to use a lower sampling frequency for each of the signal segments while maintaining a high fidelity permits the use of a converter for each signal segment that is operating at a relatively slow rate. Accordingly, a plurality of relatively inexpensive and simple converters operating at relatively slow rates can be utilized to achieve the same rate of conversion as a single relatively high speed converter converting the entire signal with little, if any, compromise in fidelity.
- the means for decomposing the signal into a number of signal segments and the means for combining the processed signal segments to form the composite signal can include any number of suitable signal decomposing or combining devices (e.g., filters, analog circuitry, computer software, digital circuitry and optical filters).
- a plurality or bank of analog or digital analysis filters is used to perform signal decomposition and a plurality or bank of analog or digital synthesis filters is used to perform signal reconstruction.
- the analysis and synthesis filters can be implemented in any number of ways depending upon the type of signal to be filtered. Filtration can be by, for example, analog, digital, acoustic, and optical filtering methods.
- the filters can be designed as simple delays or very sophisticated filters with complex amplitude and phase responses.
- a plurality or bank of analysis and/or synthesis filters preferably designed for perfect reconstruction, is used to process the signal segments.
- perfect reconstruction occurs when the composite signal, or output of the synthesis filter bank, is simply a delayed version of the source signal.
- the analysis filters and synthesis filters are represented in a special form known as the Polyphase representation.
- Noble identities are can be used to losslessly move the decimators to the left of the analysis filters and the interpolators to the right of the synthesis filters.
- noise components in each of the signal segments can be removed prior to signal analysis or conversion in the processing step.
- the removal of noise prior to analog-to-digital conversion can provide significant additional reductions in computational requirements.
- a coded signal is acquired rapidly using the above-referenced invention.
- the signal segments are correlated with a corresponding plurality of replicated signals to provide a corresponding plurality of correlation functions defining a plurality of peaks; an amplitude, time delay, and phase delay are determined for at least a portion of the plurality of peaks; and at least a portion of the signal defined by the signal segments is realigned and scaled based on one or more of the amplitude, time delay, and phase delay for each of the plurality of peaks.
- a method for reducing noise in a signal expressed by a random or pseudorandom waveform includes the steps of decomposing the signal into a plurality of signal segments and removing a noise component from each of the signal segments to form a corresponding plurality of processed signal segments.
- the means for decomposing the signal can be any of the devices noted above, and the means for removing the noise component includes a noise reducing quantizer, noise filters and rank reduction.
- Signal reconstruction may or may not be used to process further the processed signal segments. This embodiment is particularly useful in acquiring analog signals.
- synthesis filtering is performed on each of the plurality of signal segments.
- the means for performing synthesis filtering can be any of the devices noted above.
- a system can include, in addition to the synthesis filtering means, means for emitting the plurality of signal segments from a plurality of signal sources (e.g., antennas); means for receiving each of the plurality of signal segments (e.g., antennas); and means for converting each of the signal segments from analog format to digital format (e.g., analog-to-digital converter).
- a plurality of signal sources e.g., antennas
- means for receiving each of the plurality of signal segments e.g., antennas
- means for converting each of the signal segments from analog format to digital format e.g., analog-to-digital converter
- the system includes: a plurality of analysis filters to decompose a source signal into a plurality of decomposed signal segments; a plurality of digital-to-analog conversion devices for converting the plurality of decomposed signal segments from digital into analog format to form a corresponding plurality of analog signal segments; a plurality of amplifiers to form a corresponding plurality of signal segments; a plurality of signal emitters for emitting the plurality of signal segments; and a plurality of receptors for receiving the plurality of signal segments.
- the system includes: a plurality of analysis filters to decompose a source signal into a plurality of decomposed signal segments; a plurality of amplifiers to amplify the decomposed signal segments to form a corresponding plurality of signal segments; a plurality of signal emitters for emitting the plurality of signal segments; and a plurality of receptors for receiving the plurality of signal segments.
- a method in which digital signals are decomposed, processed, and then recombined.
- Signal processing can include signal correlation (e.g., signal modulation or demodulation), and oblique projection filtration (e.g., as described in copending U.S. patent application Ser. No. 08/916,884 filed Aug. 22, 1997, entitled “RAKE Receiver For Spread Spectrum Signal Demodulation,” which is incorporated herein fully by reference).
- FIG. 1 depicts a first embodiment of the present invention
- FIG. 2 depicts an analog signal
- FIG. 3 depicts the analog signal of FIG. 2 divided up into a plurality of signal segments
- FIG. 4 depicts the first embodiment including decimation
- FIGS. 5A and 5B depict noble identities
- FIG. 6 depicts a polyphase filter representation
- FIG. 7 depicts a polyphase filter representation with noble identities
- FIG. 8 depicts another embodiment of the present invention.
- FIG. 9 depicts the quantization process of the quantizers in FIG. 8;
- FIG. 10 depicts a subband digital transmitter
- FIG. 11 depicts a subband analog transmitter
- FIG. 12 depicts a subband receiver
- FIG. 13 depicts rank reduction for noise filtering
- FIG. 14 depicts another embodiment of the present invention.
- FIG. 15 depicts another embodiment of the present invention.
- FIG. 16 depicts RAKE processing
- FIG. 17 depicts a multiplexed radar transmitter architecture
- FIG. 18 depicts a radar receiver architecture
- FIG. 19 depicts a digital communications example of a recursive, adaptive Wiener filter
- FIG. 20 depicts an alternative RAKE processing methodology
- FIG. 21 depicts a least squares, multiple input multiple output filter design problem.
- a wideband, pseudorandom or random signal 40 (shown in FIG. 2) is passed to a bank or plurality of analysis filters 44 a-n.
- the signal 40 has a frequency band or domain, F s , having frequency bounds, f o (lower) and f n (upper), and therefore a bandwidth of f o -f n (FIG. 2).
- the bandwidth commonly is at least about 1 kHz, more commonly at least about 1 GHz.
- Each of the analysis filters 44 a-n pass only a portion of the frequency band of the signal to form a plurality of subband signals 48 a-n, or time frequency components, characterized by discrete portions of the frequency band, F s , of the signal 40 (FIG. 3).
- the summation of the individual frequency bandwidths of all of the subband signals 48 a-n is substantially the same as the bandwidth of the signal 40 (FIG. 3).
- the various subband signals 48 a-n are processed 52 a-n independently as described below to form a corresponding plurality of processed signal segments 56 a-n.
- the processed signal segments 56 a-n are passed to a bank or plurality of synthesis filters 60 a-n and combined to form a composite signal 64 .
- the signal 40 is analog or digital and, when the signal 40 is analog, the composite signal 64 is digital, and, when the signal 40 is digital, the composite signal 64 is analog.
- the analysis and synthesis filters 44 a-n and 60 a-n can be in any of a number of configurations provided that the filters pass only discrete, or at most only slightly overlapping, portions of the frequency domain of the signal 40 . It is preferred that the frequency bands of the subband signals overlap as little as possible. Preferably, no more than about 5% and more preferably no more than about 1% of the frequency bands of adjacent subband signals overlap.
- the filters can be analog or digital depending on the type of signal 40 or the processed signal segments 56 a-n.
- suitable analog analysis and synthesis filters include a suitably configured bandpass filter formed by one or more low pass filters, one or more high pass filters, a combination of band reject and low pass filters, a combination of band reject and high pass filters, or one or more band reject filters.
- Digital analysis and synthesis filters are typically defined by software architecture that provides the desired filter response.
- the signal 40 is decomposed by the analysis filter bank 46 (which includes analog or digital analysis filters H k (Z) 44 a-n ) into subband signals which are each sampled by a downsampler 64 a-n performing an M-fold decimation (i.e., taking every M th sample), and the sampled subband signals are further sampled after signal processing by an up-sampler 68 a-n (and/or expander (which fills in L-1 zeros in between each sample)) and the further sampled subband signals are combined by a synthesis filter bank 62 (that includes analog or digital synthesis filters G k (z) 60 a-n ).
- the sampled subband signals denoted by x o (n), x 1 (n), . . . x m ⁇ 1 (n), are the outputs of the N-band analysis filter bank and the inputs to the N-band synthesis filter bank. As a result of decimation, the subband signals are 1/N the rate of the input rate of the signal 40 .
- the subband signals 48 a-n can be downsampled without any loss in fidelity of the output signal. This downsampling is permissible because the subband signals are of narrow bandwidth and the consequence of the downsampling is that any processing application 52 a-n that is embedded in the subbands can run at significantly reduced rates.
- a perfect reconstruction filter system can be formed by a number of different methods, including quadrature mirror filter techniques.
- a preferred technique for designing a filter bank is known as a least squares multiple input multiple output filter design notation.
- a rational transfer matrix defining one of the filter banks is known, i.e., either H(z) or G T (z), along with a rational transfer matrix F(z) defining the ideal output of the filter banks.
- H(z) and F(z) are the known rational transfer matrices
- the unknown rational transfer matrix, G T (z) is determined by the following equation:
- H(z) H 0 (z) U(z); [H 0 (z) is the minimum phase equivalent of H(z)]
- the rational transfer matrices of the analysis and/or synthesis filters are mathematically expressed in a polyphase filter representation.
- Type 2 polyphase filter representation (known as Type 2 polyphase filter representation).
- Noble identities can be used to losslessly move the decimators to the left of the analysis filters and the L-fold up-sampler and/or expander to the right of the synthesis filters. In this manner, the analysis and synthesis filters operate on lower rate data, thereby realizing significant computational savings.
- the noble identities include:
- FIR finite impulse response
- H ( z ) H o ( z 2 )+ H 1 ( z 2 )
- FIG. 6 is a polyphase representation based implementation of H(z) without noble identities
- FIG. 7 is a polyphase representation-based implementation of the analysis filters H(z) using noble identities to move the decimators ahead of the analysis filters.
- H o (z 2 ) and H 1 (z 2 ) operate at half the rate as compared to H(z) and therefore have two units of time in which to perform all the necessary computations, and the components are continually active (i.e., there are no resting times). Accordingly, there is an M-fold reduction in the number of multiplications and additions per unit of time when using both polyphase representation and the noble identities to implement an M-fold decimation filter.
- Subband signal processing can take a variety of forms.
- the source signal 40 and subband signals 48 a-n are in analog form and a plurality of quantizers or analog-to-digital converters are used to convert the subband signals 48 a-n to digital form before further processing 82 (e.g., correlation for encoded subband signals, subband signal digital beamforming in multiple antenna systems, etc.) and/or synthesis of the digital subband signals 78 a-n is performed.
- the subband signals 48 a-n are preferably sampled by each of the decimators or downsamplers 64 a-n at a rate of at least about twice the bandwidth of the corresponding subband signal 48 a-n to maintain fidelity.
- each quantizer, or analog-to-digital converter, 74 a-n determines the digital word or representation 90 a-n that corresponds to the bin 86 a-n having boundaries capturing the amplitude of the analog subband signal at that time and outputs the digital word or representation that represents the selected quantization level assigned to the respective bin.
- the digital subband signals 78 a-n are converted 94 a-n from radio frequency (RF) to base band frequency and optionally subjected to further signal processing 60 .
- the processed subband signals 98 are formed into a digital composite signal 102 by the synthesis filter bank 60 .
- noise rejecting quantizers can be utilized as the quantizers 74 a-n.
- a noise rejecting quantizer assigns more bits to the portions of the subband signal having less noise (and therefore more signal) and fewer bits to the noisy portion. This selective assignment is accomplished by adaptively moving the bin boundaries so as to narrow the bin width (thereby increasing quantization fidelity.
- t k x k - 1 + x k 2 + ⁇ 2 ⁇ ( x k ) - ⁇ 2 ⁇ ( x k - 1 ) 2 ⁇ ( x k - x k - 1 ) ;
- ⁇ x k e k - 1 2 ⁇ ⁇ ⁇ 2 ⁇ ( x k ) ⁇ x k
- x is the signal to be quantized
- N is the number of quantization levels
- 74. k is signal identifier
- ⁇ is the noise covariance
- MSE mean squared quantization error
- ⁇ t k ⁇ o N ⁇ 1 are the bin thresholds
- f y (y) is the probability density function of y
- LM Lloyd-Max
- the noise covariance, ⁇ can be estimated by linear mean squared error estimation techniques.
- Linear mean squared error estimates are characterized by the following equation:
- T is the Wiener filter
- R xy is the cross covariance between x and y
- R yy is the covariance of y.
- R xy and R yy are unknown and require estimation.
- a number of techniques can be used to estimate R xy and R yy , including an adaptive Wiener filter (e.g., using the linear mean squared algorithm), direct estimation, sample matrix inversion and a recursive, adaptive Wiener filter, with a recursive, adaptive Wiener filter being more preferred.
- ⁇ acute over (T) ⁇ M+1 X M Y M * ⁇ M+1 ⁇ 1 +xy* ⁇ M+1 ⁇ 1
- the transmitter sends a signal x, which corresponds to a data bit.
- the receiver observes the corresponding y and uses it to estimate x using ⁇ acute over (T) ⁇ M :
- the receiver determines r 2 , cos 2 ⁇ and sin 2 ⁇ .
- FIG. 10 depicts a subband digital transmitter according to this embodiment.
- the signal 100 is in digital format and is transmitted to a bank of analysis filters 104 a-n to form a plurality of digital subband signals 108 a-n; the digital subband signals 108 a-n are processed by digital-to-analog converters 112 a-n to form analog subband signals 116 a-n; the analog subband signals 116 a-n are amplified by amplifiers 120 a-n to form amplified subband signals 124 a-n; and the amplified subband signals 124 a-n transmitted via antennas 128 a-n.
- a subband analog transmitter is depicted where the signal 140 is analog and not digital.
- the signal 140 is decomposed into a plurality of analog subband signals 144 a-n by analog analysis filters 148 a-n and the analog subband signals 144 a-n amplified by amplifiers 152 a-n, and the amplified subband signals transmitted by antennas 156 a-n.
- a subband receiver is depicted that is compatible with the subband analog transmitter of FIG. 11.
- a plurality of subband signals 160 a-n are received by a plurality of antennas 164 a-n, the received subband signals 168 a-n down converted from radio frequency to baseband frequency by down converters 172 a-n; the down converted subband signals 176 a-n which are in analog form are converted by quantizers 180 a-n from analog to digital format; and the digital subband signals 184 a-n combined by synthesis filters 188 a-n to form the digital composite signal 192 .
- the subband signals when the subband signals are encoded waveforms such as Code Division Multiple Access (CDMA) or precision P(Y) GPS code signals, the subband signals can be encoded or decoded to realize computational savings.
- the subband signals are correlated with a replica of the transmitted signal prior to detection.
- the correlation process can be performed before or after synthesis filtering or before conversion to digital (and therefore in analog) or after conversion to digital (and therefore in digital).
- the approach is particularly useful for the rapid, direct acquisition of wideband pseudorandom noise encoded waveforms, like CDMA type signals and the P(Y) GPS code, in a manner that is robust with respect to multipath effects and wide-band noise. Because the M-subband signals have narrow bandwidths and therefore can be searched at slower rates, correlation of the subband signals rather than the signal or the composite signal can be performed with over an M-fold reduction in computation and therefore reduce the individual component cost.
- the number of subbands requiring correlation at any trial time and Doppler frequency can be reduced.
- the pseudorandom nature of the coded signals implies that a coded signal will only lie in certain known subbands at any given time.
- subbands 200 a-j outside of the subbands 204 a-j containing the coded signal can be eliminated to reduce the effects of wide-band noise in the acquisition and/or tracking of pseudorandom signals. This is accomplished by eliminating any subband in which the noise component exceeds the signal component (i.e., the SNR is less than 1).
- the replicated code 208 from the code generator 212 must be passed through an analysis filter bank 216 that is identical to the analysis filter bank 220 used to decompose the signal 224 . Because the correlation must be performed for different segments of the replicated code 208 , each indexed by some start time, this decomposition is necessary for all trial segments of the replicated code 208 .
- a plurality of subband correlators 228 a-n receive both the subband signals 232 a-n and the replicated subband signals 236 a-n and generate a plurality of subband correlation signals 240 a-n.
- q(k) is the subband correlation signal
- p n (i) (k) is the component of the i th trial segment of the P(Y) code in the n th subb and;
- x m (k) is the component of the measurement that lies in the m th subband
- N is the number of samples over which the correlation is performed.
- the subband correlation signals 240 a-n are upsampled and interpolated by the synthesis filters 244 a-n and then squared and combined.
- the resulting composite signal 248 is the correlation function that can be further processed and detected.
- the signals can be processed by a RAKE processor, which is commonly a maximal SNR combiner, to align in both time and phase multipath signals before detection and thereby provide improved signal-to-noise ratios and detection performance.
- a RAKE processor which is commonly a maximal SNR combiner, to align in both time and phase multipath signals before detection and thereby provide improved signal-to-noise ratios and detection performance.
- a signal can be fragmented and arrive at a receiver via multiple paths (i.e., multipath signals) due to reflections from other objects, particularly in urban areas.
- the formation of a number of multipath signals from a source signal can degrade the correlation peaks, which contributes to the degradation of the detections.
- the RAKE processor determines the time and phase delays of these multipath signals by searching for correlation peaks in the correlation function and identifying the time and phase delays for each of the peaks.
- the RAKE processor uses the time and phase delay estimates to realign the multipath signals so that they can add constructively and enhance the correlation peaks.
- the peak enhancement improves detection because of the increase in signal-to-noise ratio.
- FIG. 15 depicts an embodiment of a signal processing architecture incorporating these features.
- the signals 300 are received by one or more antennas 304 , down converted by a down converter 308 to intermediate frequency, filtered by one or more filters 312 , and passed through an analog-to-digital converter 316 to form a digital signal 320 .
- the digital signal 320 is passed through an analysis filter bank 324 to generate a plurality of subband signals 328 a-n, and the subband signals 328 a-n to a plurality of subband correlators 332 a-n as noted above to form a plurality of subband correlation signals 336 a-n.
- the subband correlation signals 336 a-n are passed to a synthesis filter bank 340 to form a correlation function 344 corresponding to the signal 300 .
- the correlation function 344 is passed to a pre-detector 348 to determine an estimated transmit time and frequency and an amplitude and delay for each of the correlation peaks.
- the estimated transmit time and frequency 352 are provided to a code generator 356 and the amplitude and time delay 360 associated with each correlation peak are provided to the RAKE processor 364 .
- the code generator 356 determines a replicated code 368 corresponding to the signal 300 based on the estimated trial time and frequency. Using the correlation peak amplitudes and time and/or phase delays, the RAKE processor 364 , as shown in FIG.
- p is the number of multipath signals (and therefore number of peaks);
- a i is the amplitude of the i th peak
- t i is the time delay of the i th peak
- ⁇ is the phase delay of the i th peak
- y(k) is the input sequence into the code correlator.
- the RAKED signal 372 and the replicated code 368 are correlated in a correlator 376 to provide the actual transmit time and frequency 380 which are then used by detector 384 to detect the signal.
- the radar signals 400 a-n are a number of coded waveforms that operate in separate, contiguous subbands (referred to as “radar subband signals”). As shown in FIG. 17, the radar signals 40 are simultaneously transmitted by a plurality of transmitters 404 a-n that each include a plurality of analysis filters (not shown) to form the various radar subband signals 400 a-n. Referring to FIG. 18, the various radar subband signals 400 a-n are received by a signal receptor 410 and passed through a plurality of bandpass filters 414 a-n.
- a bandpass filter 414 a-n having unique bandpass characteristics corresponds to each of the radar subband signals.
- the various filtered subband signals 416 a-n are sampled by a plurality of decimators 422 a-n and quantized by a plurality of quantizers 426 a-n to form digital subband signals 430 a-n.
- the digital subband signals 430 a-n are analyzed by a plurality of detectors 434 a-n to form a corresponding plurality of detected signals 438 a-n.
- the detectors 434 a-n use a differently coded waveform for each of the transmitted radar subband signals 400 a-n so that the subband radar signals can be individually separated upon reception. As noted above in FIGS.
- the coded radar waveform is decomposed by a plurality of analysis filters (not shown) that are identical to the analysis filters in the receiver to provide replicated subband signals to the detectors 434 a-n.
- Each detector 434 a-n correlates a radar subband signal 430 a-n with its corresponding replicated subband signal to form a plurality of corresponding detected signals 438 a-n.
- the detected signals 438 a-n are analyzed by a synthesis filter bank 412 a-n to form a composite radar signal 446 .
- a bank of analysis filters and synthesis filters can be implemented both directly before and after the correlation step (not shown) to provide the above-noted reductions in computational requirements.
- the analysis filters can be relocated before the analog-to-digital converter 316 to form the subband signals before as opposed to after conversion.
- the RAKE processor 364 can account for the relative delays in antenna outputs of the signal 300 (which is a function of the arrangement of the antennas as well as the angular location of the signal source) by summing the antenna outputs without compensating for the relative output delays.
- the correlation process may result in N ⁇ p peaks, where N is the number of antenna outputs and p is the number of multipath induced peaks.
- the Np peaks are then used to realign and scale the input data before summation.
- the RAKE 364 in effect has performed the phase-delay compensation usually done in beam-steering.
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Compression, Expansion, Code Conversion, And Decoders (AREA)
Abstract
The method and apparatus of the present invention is directed to architectures for signal processing, such as for performing analog-to-digital and digital-to-analog conversions, in which the source signal is decomposed into subband signals by an analysis filter, processed, and the processed subband signals combined to form a reconstructed signal that is representative of the source signal.
Description
- 1. The present application claims priority from U.S. Provisional Application Serial Nos. 60/087,036 filed May 28, 1998; 60/056,455 filed Aug. 21, 1997; and 60/056,228 filed Aug. 21, 1997, all of which are incorporated herein by this reference.
- 2. The present invention relates generally to a method and apparatus for acquiring wide-band random and pseudorandom noise encoded waveforms and specifically to a method and apparatus for acquiring wide-band signals, including deterministic signals, random signals and pseudorandom noise encoded waveforms that divides the waveform into a plurality of subbands prior to signal processing thereof.
- 3. Analog-to-digital converters are devices that convert real world analog signals into a digital representation or code which a computer can thereafter analyze and manipulate. Analog signals represent information by means of continuously variable physical quantities while digital signals represent information by means of differing discrete physical property states. Converters divide the full range of the analog signal into a finite number of levels, called quantization levels, and assigns to each level a digital code. The total number of quantization levels used by the converter is an indication of its fidelity and is measured in terms of bits. For example, an 8-bit converter uses 28 or 256 levels, while a 16-bit converter uses 216 or 65536 levels.
- 4. During the conversion process, the converter determines the quantization level that is closest to the amplitude of the analog signal at that time and outputs the digital code that represents the selected quantization level. The rate at which the output is created indicates the speed of the converter and is measured in terms of samples per second (sps) or frequency in Hertz (Hz). As will be appreciated, a larger number of bits and therefore quantization levels equates into a finer representation of the analog signal.
- 5. In designing an analog-to-digital converter, there are a number of considerations. In many applications for example it is desirable that the converter has not only a high rate of speed but also a large number of quantization levels or a high degree of fidelity. Such converters are difficult to build and therefore tend to be highly complex and very expensive. The key reason is that conversion errors and the consequential device layout constraints for reducing such errors, both of which can be ignored at slow speeds, can become significant at high speeds. As a result, in existing converters, high fidelity and high speed are commonly mutually exclusive; that is, the higher the converter speed the lower the converter fidelity and vice versa.
- 6. It is an object of the present invention to provide an analog-to-digital converter that has a high fidelity and a high speed. Related objectives are to provide such an analog-to-digital converter that is relatively simple and inexpensive.
- 7. The present invention is directed to a method and apparatus for processing signals, particularly wide-band signals, including deterministic signals, random signals, and signals defined by pseudorandom waveforms with a relatively high degree of fidelity and efficiency at a high speed and at a low cost. The invention is particularly useful for processing wideband signal, including signals defined by broadband signals (i.e., signals having a bandwidth of preferably more than about 1 kHz and more preferably more than about 1 GHz).
- 8. The signal can be in any suitable form such as electromagnetic radiation, acoustic, electrical and optical.
- 9. In one embodiment, the method includes the following steps:
- 10. (a) decomposing the analog or digital signal into a plurality of signal segments (i.e., subband signals), each signal segment having a signal segment bandwidth that is less than the signal bandwidth;
- 11. (b) processing each of the signal segments to form a plurality of processed signal segments; and
- 12. (c) combining the processed signal segments into a composite signal that is digital when the signal is analog and analog when the signal is digital. As will be appreciated, the sum of the plurality of signal bandwidths is approximately equivalent to the signal bandwidth. The means for processing the signal segments can include any number of operations, including filtering, analog-to-digital or digital-to-analog conversion, signal modulation and/or demodulation, object tracking, RAKE processing, beamforming, null steering, correlation, interference-suppression and matched subspace filtering.
- 13. In a particularly preferred application, the signal processing step (b) includes either analog-to-digital or digital-to-analog conversions. The use of signal segments rather than the entire signal for such conversions permits the use of a lower sampling rate to retain substantially all of the information present in the source signal. According to the Bandpass Sampling Theorem, the sampling frequency of the source signal should be at least twice the bandwidth of the source signal to maintain a high fidelity. The ability to use a lower sampling frequency for each of the signal segments while maintaining a high fidelity permits the use of a converter for each signal segment that is operating at a relatively slow rate. Accordingly, a plurality of relatively inexpensive and simple converters operating at relatively slow rates can be utilized to achieve the same rate of conversion as a single relatively high speed converter converting the entire signal with little, if any, compromise in fidelity.
- 14. The means for decomposing the signal into a number of signal segments and the means for combining the processed signal segments to form the composite signal can include any number of suitable signal decomposing or combining devices (e.g., filters, analog circuitry, computer software, digital circuitry and optical filters). Preferably, a plurality or bank of analog or digital analysis filters is used to perform signal decomposition and a plurality or bank of analog or digital synthesis filters is used to perform signal reconstruction. The analysis and synthesis filters can be implemented in any number of ways depending upon the type of signal to be filtered. Filtration can be by, for example, analog, digital, acoustic, and optical filtering methods. By way of example, the filters can be designed as simple delays or very sophisticated filters with complex amplitude and phase responses.
- 15. In a preferred configuration, a plurality or bank of analysis and/or synthesis filters, preferably designed for perfect reconstruction, is used to process the signal segments. As will be appreciated perfect reconstruction occurs when the composite signal, or output of the synthesis filter bank, is simply a delayed version of the source signal.
- 16. In one configuration, the analysis filters and synthesis filters are represented in a special form known as the Polyphase representation. In this form, Noble identities are can be used to losslessly move the decimators to the left of the analysis filters and the interpolators to the right of the synthesis filters.
- 17. In another configuration, noise components in each of the signal segments can be removed prior to signal analysis or conversion in the processing step. The removal of noise prior to analog-to-digital conversion can provide significant additional reductions in computational requirements.
- 18. In yet another configuration, a coded signal is acquired rapidly using the above-referenced invention. In the processing step, the signal segments are correlated with a corresponding plurality of replicated signals to provide a corresponding plurality of correlation functions defining a plurality of peaks; an amplitude, time delay, and phase delay are determined for at least a portion of the plurality of peaks; and at least a portion of the signal defined by the signal segments is realigned and scaled based on one or more of the amplitude, time delay, and phase delay for each of the plurality of peaks.
- 19. In another embodiment, a method is provided for reducing noise in a signal expressed by a random or pseudorandom waveform. The method includes the steps of decomposing the signal into a plurality of signal segments and removing a noise component from each of the signal segments to form a corresponding plurality of processed signal segments. The means for decomposing the signal can be any of the devices noted above, and the means for removing the noise component includes a noise reducing quantizer, noise filters and rank reduction. Signal reconstruction may or may not be used to process further the processed signal segments. This embodiment is particularly useful in acquiring analog signals.
- 20. In yet a further embodiment, a method is provided for combining a plurality of signal segments (which may or may not be produced by analysis filters). In the method, synthesis filtering is performed on each of the plurality of signal segments. The means for performing synthesis filtering can be any of the devices noted above.
- 21. A number of differing system configurations can incorporate the synthesis filtering means in this embodiment of the invention. For example, a system can include, in addition to the synthesis filtering means, means for emitting the plurality of signal segments from a plurality of signal sources (e.g., antennas); means for receiving each of the plurality of signal segments (e.g., antennas); and means for converting each of the signal segments from analog format to digital format (e.g., analog-to-digital converter).
- 22. In another configuration, the system includes: a plurality of analysis filters to decompose a source signal into a plurality of decomposed signal segments; a plurality of digital-to-analog conversion devices for converting the plurality of decomposed signal segments from digital into analog format to form a corresponding plurality of analog signal segments; a plurality of amplifiers to form a corresponding plurality of signal segments; a plurality of signal emitters for emitting the plurality of signal segments; and a plurality of receptors for receiving the plurality of signal segments.
- 23. In yet another configuration, the system includes: a plurality of analysis filters to decompose a source signal into a plurality of decomposed signal segments; a plurality of amplifiers to amplify the decomposed signal segments to form a corresponding plurality of signal segments; a plurality of signal emitters for emitting the plurality of signal segments; and a plurality of receptors for receiving the plurality of signal segments.
- 24. In another embodiment, a method is provided in which digital signals are decomposed, processed, and then recombined. Signal processing can include signal correlation (e.g., signal modulation or demodulation), and oblique projection filtration (e.g., as described in copending U.S. patent application Ser. No. 08/916,884 filed Aug. 22, 1997, entitled “RAKE Receiver For Spread Spectrum Signal Demodulation,” which is incorporated herein fully by reference).
- 25.FIG. 1 depicts a first embodiment of the present invention;
- 26.FIG. 2 depicts an analog signal;
- 27.FIG. 3 depicts the analog signal of FIG. 2 divided up into a plurality of signal segments;
- 28.FIG. 4 depicts the first embodiment including decimation;
- 29.FIGS. 5A and 5B depict noble identities;
- 30.FIG. 6 depicts a polyphase filter representation;
- 31.FIG. 7 depicts a polyphase filter representation with noble identities;
- 32.FIG. 8 depicts another embodiment of the present invention;
- 33.FIG. 9 depicts the quantization process of the quantizers in FIG. 8;
- 34.FIG. 10 depicts a subband digital transmitter;
- 35.FIG. 11 depicts a subband analog transmitter;
- 36.FIG. 12 depicts a subband receiver;
- 37.FIG. 13 depicts rank reduction for noise filtering;
- 38.FIG. 14 depicts another embodiment of the present invention;
- 39.FIG. 15 depicts another embodiment of the present invention;
- 40.FIG. 16 depicts RAKE processing;
- 41.FIG. 17 depicts a multiplexed radar transmitter architecture;
- 42.FIG. 18 depicts a radar receiver architecture;
- 43.FIG. 19 depicts a digital communications example of a recursive, adaptive Wiener filter;
- 44.FIG. 20 depicts an alternative RAKE processing methodology; and
- 45.FIG. 21 depicts a least squares, multiple input multiple output filter design problem.
- 46. Referring to FIG. 1, an embodiment of the present invention is illustrated. As can be seen from FIGS. 1 and 2, a wideband, pseudorandom or random signal 40 (shown in FIG. 2) is passed to a bank or plurality of
analysis filters 44 a-n. Thesignal 40 has a frequency band or domain, Fs, having frequency bounds, fo (lower) and fn (upper), and therefore a bandwidth of fo-fn (FIG. 2). The bandwidth commonly is at least about 1 kHz, more commonly at least about 1 GHz. Each of the analysis filters 44 a-n pass only a portion of the frequency band of the signal to form a plurality ofsubband signals 48 a-n, or time frequency components, characterized by discrete portions of the frequency band, Fs, of the signal 40 (FIG. 3). As will be appreciated, the summation of the individual frequency bandwidths of all of the subband signals 48 a-n is substantially the same as the bandwidth of the signal 40 (FIG. 3). Thevarious subband signals 48 a-n are processed 52 a-n independently as described below to form a corresponding plurality of processed signal segments 56 a-n. The processed signal segments 56 a-n are passed to a bank or plurality ofsynthesis filters 60 a-n and combined to form acomposite signal 64. Generally, thesignal 40 is analog or digital and, when thesignal 40 is analog, thecomposite signal 64 is digital, and, when thesignal 40 is digital, thecomposite signal 64 is analog. - 47. The analysis and
synthesis filters 44 a-n and 60 a-n can be in any of a number of configurations provided that the filters pass only discrete, or at most only slightly overlapping, portions of the frequency domain of thesignal 40. It is preferred that the frequency bands of the subband signals overlap as little as possible. Preferably, no more than about 5% and more preferably no more than about 1% of the frequency bands of adjacent subband signals overlap. - 48. The filters can be analog or digital depending on the type of
signal 40 or the processed signal segments 56 a-n. Examples of suitable analog analysis and synthesis filters include a suitably configured bandpass filter formed by one or more low pass filters, one or more high pass filters, a combination of band reject and low pass filters, a combination of band reject and high pass filters, or one or more band reject filters. Digital analysis and synthesis filters are typically defined by software architecture that provides the desired filter response. - 49. In a preferred configuration shown in FIG. 4, the
signal 40 is decomposed by the analysis filter bank 46 (which includes analog or digital analysis filters Hk(Z) 44 a-n) into subband signals which are each sampled by adownsampler 64 a-n performing an M-fold decimation (i.e., taking every Mth sample), and the sampled subband signals are further sampled after signal processing by an up-sampler 68 a-n (and/or expander (which fills in L-1 zeros in between each sample)) and the further sampled subband signals are combined by a synthesis filter bank 62 (that includes analog or digital synthesis filters Gk(z) 60 a-n). The sampled subband signals, denoted by xo(n), x1(n), . . . xm−1(n), are the outputs of the N-band analysis filter bank and the inputs to the N-band synthesis filter bank. As a result of decimation, the subband signals are 1/N the rate of the input rate of thesignal 40. - 50. Preferably, the analysis and synthesis filters are perfect reconstruction filters such that the
composite signal 64 is a delayed version of the signal 40 (i.e., y(n)=u(n−L) where y(n) is the composite signal, u(n) is the signal, and L is time of delay). Using perfect reconstruction filters, the subband signals 48 a-n can be downsampled without any loss in fidelity of the output signal. This downsampling is permissible because the subband signals are of narrow bandwidth and the consequence of the downsampling is that any processing application 52 a-n that is embedded in the subbands can run at significantly reduced rates. - 51. As will be appreciated, a perfect reconstruction filter system can be formed by a number of different methods, including quadrature mirror filter techniques. A preferred technique for designing a filter bank is known as a least squares multiple input multiple output filter design notation. According to this technique, which is illustrated in FIG. 21, a rational transfer matrix defining one of the filter banks is known, i.e., either H(z) or GT(z), along with a rational transfer matrix F(z) defining the ideal output of the filter banks. Assuming that H(z) and F(z) are the known rational transfer matrices, the unknown rational transfer matrix, GT(z), is determined by the following equation:
- G T(z)=[F(z)U T(z −1)]+H 0 −1(z)
- 52. where
- 53. H(z)=H0(z) U(z); [H0(z) is the minimum phase equivalent of H(z)]
- 54. U(z)UT(z−1)=I; Paraunitary
- 55. [F(z)UT(z−1)]x: Causal part of F(z)UT(z−1)
- 56. As will be appreciated if GT(z) were known and H(z) were unkown, then the equation would be solved for H(z) rather than GT(z), and GT(z) would be decomposed into the following:
- G T(z)=G o T(z)U(z)
- 57. where Go T(z) is the minimum phase equivalent of GT(z).
-
- 59. where
-
- e l(n)=h(Mn+l), 0≦l≦M−1
-
- 62. where
- R 1(z M)=E M−1−l(z)
- 63. (known as
Type 2 polyphase filter representation). As will be appreciated, other techniques exist for expressing a rational transfer matrix defining a filter system including impluse response and filter description. - 64. Noble identities can be used to losslessly move the decimators to the left of the analysis filters and the L-fold up-sampler and/or expander to the right of the synthesis filters. In this manner, the analysis and synthesis filters operate on lower rate data, thereby realizing significant computational savings. The noble identities include:
- 65. Identity I: Decimation by M followed by filtering defined by the mathematical function H(z) is equivalent to filtering by H(zM) followed by decimation by M (FIG. 5A).
- 66. Identity II: Filtering by G(z) followed by an upsampling by L is equivalent to upsampling by L followed by filtering by G(zL) (FIG. 5B).
- 67. By way of example, assume H(z) defines an order N finite impulse response (FIR) digital analysis filter with impulse response h(n), M=2, u(n) is the source signal and X(n) is the subband signal. Using the
type 1 polyphase representation above, H(z) is decomposed to yield the following: - H(z)=H o(z 2)+H 1(z 2)
- 68. Based on the foregoing, FIG. 6 is a polyphase representation based implementation of H(z) without noble identities and FIG. 7 is a polyphase representation-based implementation of the analysis filters H(z) using noble identities to move the decimators ahead of the analysis filters. In this configuration, Ho(z2) and H1(z2) are FIR filters of order no+1 and n1+1, where N=no+n1+1. Ho(z2) and H1(z2) operate at half the rate as compared to H(z) and therefore have two units of time in which to perform all the necessary computations, and the components are continually active (i.e., there are no resting times). Accordingly, there is an M-fold reduction in the number of multiplications and additions per unit of time when using both polyphase representation and the noble identities to implement an M-fold decimation filter.
- 69. Subband signal processing can take a variety of forms. In one embodiment shown in FIG. 8 which depicts a receiver and antenna architecture, the
source signal 40 andsubband signals 48 a-n are in analog form and a plurality of quantizers or analog-to-digital converters are used to convert the subband signals 48 a-n to digital form before further processing 82 (e.g., correlation for encoded subband signals, subband signal digital beamforming in multiple antenna systems, etc.) and/or synthesis of the digital subband signals 78 a-n is performed. As noted above, the subband signals 48 a-n are preferably sampled by each of the decimators ordownsamplers 64 a-n at a rate of at least about twice the bandwidth of thecorresponding subband signal 48 a-n to maintain fidelity. As shown in FIG. 9, each quantizer, or analog-to-digital converter, 74 a-n determines the digital word or representation 90 a-n that corresponds to the bin 86 a-n having boundaries capturing the amplitude of the analog subband signal at that time and outputs the digital word or representation that represents the selected quantization level assigned to the respective bin. The digital subband signals 78 a-n are converted 94 a-n from radio frequency (RF) to base band frequency and optionally subjected tofurther signal processing 60. The processed subband signals 98 are formed into a digital composite signal 102 by thesynthesis filter bank 60. - 70. To provide increased accuracy, noise rejecting quantizers can be utilized as the quantizers 74 a-n. As will be appreciated, a noise rejecting quantizer assigns more bits to the portions of the subband signal having less noise (and therefore more signal) and fewer bits to the noisy portion. This selective assignment is accomplished by adaptively moving the bin boundaries so as to narrow the bin width (thereby increasing quantization fidelity. An example of a design equation for a Lloyd-Max noise rejecting quantizer is as follows:
- 71. where:
- 72. x is the signal to be quantized;
- 73. N is the number of quantization levels;
- 74. k is signal identifier;
- 75. σ is the noise covariance.
-
- 77. where:
- 78. {xk}o N−1 are the representation points;
- 79. {ck}o N−1 are the quantization bins;
- 80. {tk}o N−1 are the bin thresholds;
- 81. fy(y) is the probability density function of y;
-
- 83. The LM equations require that the bin thresholds be equidistant from the representation points and that each representation point be the conditional mean of x in the corresponding quantization bin. As will be appreciated, a Lloyd-Max (LM) quantizer substantially minimizes the mean squared error between the discrete approximation of the signal and its continuous representation.
- 84. The noise covariance, δ, can be estimated by linear mean squared error estimation techniques. Linear mean squared error estimates are characterized by the following equation:
- {circumflex over (X)}=Ty=R xy R yy −1 y
- 85. where T is the Wiener filter, Rxy is the cross covariance between x and y and Ryy is the covariance of y.
- 86. Rxy and Ryy are unknown and require estimation. A number of techniques can be used to estimate Rxy and Ryy, including an adaptive Wiener filter (e.g., using the linear mean squared algorithm), direct estimation, sample matrix inversion and a recursive, adaptive Wiener filter, with a recursive, adaptive Wiener filter being more preferred.
- 87. The recursive, adaptive Wiener filter is explained in Thomas, J. K., Canonical Correlations and Adaptive Subspace Filtering, Ph.D Dissertation, University of Colorado Boulder, Department of Electrical and Compute Engineering, pp.1-110, June 1996. which is incorporated herein by reference in its entirety. In a recursive, adaptive Wiener filter assume {acute over (T)}M denotes the filter when M measurements of X and Y are used. Then {acute over (T)}M is the adaptive Wiener filter
- {acute over (T)} M =X M Y M*(Y M Y M*)−1 =Ŕ xy Ŕ yy −1,
- X M =[x 1 x 2 . . . x M ]; X M+1 =[x M x]
- Y M =[y 1 y 2 . . . y M ]; Y M+1 =[y M y]
- 88. If another measurement of x and y is taken, and one more column is added to XM and YM to build {acute over (T)}M+1:
- {acute over (T)} M+1 =X M Y M *Ŕ M+1 −1 +xy*Ŕ M+1 −1
- 89. The estimate of M+1 is {acute over (X)}M+1
- {acute over (X)} M+1 ={acute over (T)} M+1 Y M+1
-
- 91. where r2=y*ŔM −1y and {tilde over (x)}M+1={acute over (T)}My.
- 92. Based on the above, when one observes y, the best estimate of the unknown x is {tilde over (x)}, with corresponding estimation error {tilde over (E)}M+1 and covariance {tilde over (Q)}M+1. If the unknown x becomes available after a delay, then {tilde over (X)}M+1 can be updated to {acute over (x)}M+1 with error covariance ÉM+1 and covariance {tilde over (Q)}M+1. The two covariances are related by the following formula:
- 93. By way of example and as illustrated in FIG. 19, consider a digital communication application in which the modulation scheme involves transmitting x0 and x1 when
bits - 94. Once the communication link is established, the transmitter sends a signal x, which corresponds to a data bit. The receiver observes the corresponding y and uses it to estimate x using {acute over (T)}M:
- {tilde over (x)}={acute over (T)} M y
- 95. The receiver determines r2, cos2θ and sin2θ.
- 96. When cos2θ is approximately equal to 1, {tilde over (x)} is deemed to be a good estimate of x and is used to decide if a 1 or 0 was sent. If, however, cos2θ<<1, then the estimate {tilde over (x)} is scaled by cos2θ, as required by equation 14, before it is used to decide if a 1 or 0 was sent. Once the decision of 1 or 0 is made, the true x is known and can be used to build {acute over (x)} as required by equation 14 above and as illustrated in FIG. 19. The x and y are also added to the training set to update {acute over (T)}M.
- 97. In another embodiment, the
source signal 40 is digital and the analysis filters are therefore digital, signal processing is performed by a digital-to-analog converter, and the synthesis filters are analog. FIG. 10 depicts a subband digital transmitter according to this embodiment. Thesignal 100 is in digital format and is transmitted to a bank of analysis filters 104 a-n to form a plurality of digital subband signals 108 a-n; thedigital subband signals 108 a-n are processed by digital-to-analog converters 112 a-n to form analog subband signals 116 a-n; the analog subband signals 116 a-n are amplified byamplifiers 120 a-n to form amplifiedsubband signals 124 a-n; and the amplifiedsubband signals 124 a-n transmitted via antennas 128 a-n. - 98. In another embodiment shown in FIG. 11, a subband analog transmitter is depicted where the
signal 140 is analog and not digital. Thesignal 140 is decomposed into a plurality of analog subband signals 144 a-n by analog analysis filters 148 a-n and the analog subband signals 144 a-n amplified by amplifiers 152 a-n, and the amplified subband signals transmitted by antennas 156 a-n. - 99. In yet another embodiment shown in FIG. 12, a subband receiver is depicted that is compatible with the subband analog transmitter of FIG. 11. Referring to FIG. 12, a plurality of subband signals 160 a-n are received by a plurality of antennas 164 a-n, the received subband signals 168 a-n down converted from radio frequency to baseband frequency by down converters 172 a-n; the down converted subband signals 176 a-n which are in analog form are converted by quantizers 180 a-n from analog to digital format; and the digital subband signals 184 a-n combined by synthesis filters 188 a-n to form the digital
composite signal 192. - 100. In any of the above-described transmitter or receiver embodiments, when the subband signals are encoded waveforms such as Code Division Multiple Access (CDMA) or precision P(Y) GPS code signals, the subband signals can be encoded or decoded to realize computational savings. In a receiver, for example, the subband signals are correlated with a replica of the transmitted signal prior to detection. The correlation process can be performed before or after synthesis filtering or before conversion to digital (and therefore in analog) or after conversion to digital (and therefore in digital). The approach is particularly useful for the rapid, direct acquisition of wideband pseudorandom noise encoded waveforms, like CDMA type signals and the P(Y) GPS code, in a manner that is robust with respect to multipath effects and wide-band noise. Because the M-subband signals have narrow bandwidths and therefore can be searched at slower rates, correlation of the subband signals rather than the signal or the composite signal can be performed with over an M-fold reduction in computation and therefore reduce the individual component cost.
- 101. To provide further reductions in computational requirements, the number of subbands requiring correlation at any trial time and Doppler frequency can be reduced. The pseudorandom nature of the coded signals implies that a coded signal will only lie in certain known subbands at any given time. According to the rank-reduction principle and as illustrated by FIG. 13, subbands 200 a-j outside of the subbands 204 a-j containing the coded signal can be eliminated to reduce the effects of wide-band noise in the acquisition and/or tracking of pseudorandom signals. This is accomplished by eliminating any subband in which the noise component exceeds the signal component (i.e., the SNR is less than 1). Such an elimination increases the bias squared, which is the power of the signal components that are eliminated, while drastically decreasing the variance, which is the power of the noise that was eliminated. In this manner, the mean squared error between the computed correlation function and the noise-free version of the correlation function is significantly reduced.
- 102. As shown in FIG. 14 to perform the correlation in the subband signals in GPS, CDMA, and other pseudorandom or random waveform applications, the replicated code 208 from the
code generator 212 must be passed through an analysis filter bank 216 that is identical to theanalysis filter bank 220 used to decompose thesignal 224. Because the correlation must be performed for different segments of the replicated code 208, each indexed by some start time, this decomposition is necessary for all trial segments of the replicated code 208. A plurality of subband correlators 228 a-n receive both the subband signals 232 a-n and the replicated subband signals 236 a-n and generate a plurality of subband correlation signals 240 a-n. The subband correlation signals 240 a-n are provided by the following equation: - 103. where:
- 104. q(k) is the subband correlation signal;
- 105. pn (i)(k) is the component of the ith trial segment of the P(Y) code in the nth subband;
- 106. xm(k) is the component of the measurement that lies in the mth subband;
- 107. N is the number of samples over which the correlation is performed.
- 108. The subband correlation signals 240 a-n are upsampled and interpolated by the synthesis filters 244 a-n and then squared and combined. The resulting
composite signal 248 is the correlation function that can be further processed and detected. - 109. After the subband correlation signals 240 a-n are generated, the signals, for example, can be processed by a RAKE processor, which is commonly a maximal SNR combiner, to align in both time and phase multipath signals before detection and thereby provide improved signal-to-noise ratios and detection performance. As will be appreciated, a signal can be fragmented and arrive at a receiver via multiple paths (i.e., multipath signals) due to reflections from other objects, particularly in urban areas. The formation of a number of multipath signals from a source signal can degrade the correlation peaks, which contributes to the degradation of the detections. The RAKE processor determines the time and phase delays of these multipath signals by searching for correlation peaks in the correlation function and identifying the time and phase delays for each of the peaks. The RAKE processor then uses the time and phase delay estimates to realign the multipath signals so that they can add constructively and enhance the correlation peaks. The peak enhancement improves detection because of the increase in signal-to-noise ratio.
- 110.FIG. 15 depicts an embodiment of a signal processing architecture incorporating these features. Referring to FIG. 11, the
signals 300 are received by one ormore antennas 304, down converted by adown converter 308 to intermediate frequency, filtered by one ormore filters 312, and passed through an analog-to-digital converter 316 to form adigital signal 320. Thedigital signal 320 is passed through ananalysis filter bank 324 to generate a plurality of subband signals 328 a-n, and the subband signals 328 a-n to a plurality of subband correlators 332 a-n as noted above to form a plurality of subband correlation signals 336 a-n. The subband correlation signals 336 a-n are passed to asynthesis filter bank 340 to form acorrelation function 344 corresponding to thesignal 300. Thecorrelation function 344 is passed to a pre-detector 348 to determine an estimated transmit time and frequency and an amplitude and delay for each of the correlation peaks. The estimated transmit time andfrequency 352 are provided to acode generator 356 and the amplitude andtime delay 360 associated with each correlation peak are provided to theRAKE processor 364. Thecode generator 356 determines a replicatedcode 368 corresponding to thesignal 300 based on the estimated trial time and frequency. Using the correlation peak amplitudes and time and/or phase delays, theRAKE processor 364, as shown in FIG. 16, shifts the input sequence y(k) by the amounts of the multipath time and/or phase delays and then weights each shifted version by the amplitude of the peak of the correlation function corresponding to that peak to form a RAKED signal 372 (denoted by yR(k)). The RAKED sequence is commonly defined by the following mathematical equation: - 111. where:
- 112. p is the number of multipath signals (and therefore number of peaks);
- 113. Ai is the amplitude of the ith peak;
- 114. ti is the time delay of the ith peak;
- 115. φ is the phase delay of the ith peak;
- 116. y(k) is the input sequence into the code correlator. The RAKED
signal 372 and the replicatedcode 368 are correlated in acorrelator 376 to provide the actual transmit time andfrequency 380 which are then used bydetector 384 to detect the signal. - 117. There are a number of variations of the above-described system. The variations are useful in specific application such as GPS, CDMA, and radar.
- 118. In one variation of the system of FIG. 15 that is depicted in FIGS. 17-18, multiplexed radar transmitted receiver architectures are depicted. The radar signals 400 a-n are a number of coded waveforms that operate in separate, contiguous subbands (referred to as “radar subband signals”). As shown in FIG. 17, the radar signals 40 are simultaneously transmitted by a plurality of transmitters 404 a-n that each include a plurality of analysis filters (not shown) to form the various radar subband signals 400 a-n. Referring to FIG. 18, the various radar subband signals 400 a-n are received by a
signal receptor 410 and passed through a plurality ofbandpass filters 414 a-n. Abandpass filter 414 a-n having unique bandpass characteristics corresponds to each of the radar subband signals. The various filtered subband signals 416 a-n are sampled by a plurality of decimators 422 a-n and quantized by a plurality of quantizers 426 a-n to form digital subband signals 430 a-n. The digital subband signals 430 a-n are analyzed by a plurality of detectors 434 a-n to form a corresponding plurality of detected signals 438 a-n. The detectors 434 a-n use a differently coded waveform for each of the transmitted radar subband signals 400 a-n so that the subband radar signals can be individually separated upon reception. As noted above in FIGS. 14-15, the coded radar waveform is decomposed by a plurality of analysis filters (not shown) that are identical to the analysis filters in the receiver to provide replicated subband signals to the detectors 434 a-n. Each detector 434 a-n correlates a radar subband signal 430 a-n with its corresponding replicated subband signal to form a plurality of corresponding detected signals 438 a-n. The detected signals 438 a-n are analyzed by asynthesis filter bank 412 a-n to form acomposite radar signal 446. - 119. In a variation of the system of FIG. 15, a bank of analysis filters and synthesis filters can be implemented both directly before and after the correlation step (not shown) to provide the above-noted reductions in computational requirements.
- 120. In another variation of the system of FIG. 15, the analysis filters can be relocated before the analog-to-
digital converter 316 to form the subband signals before as opposed to after conversion. - 121. In another variation shown of the system of FIG. 15 that is depicted in FIG. 20, the
RAKE processor 364 can account for the relative delays in antenna outputs of the signal 300 (which is a function of the arrangement of the antennas as well as the angular location of the signal source) by summing the antenna outputs without compensating for the relative output delays. The correlation process may result in N×p peaks, where N is the number of antenna outputs and p is the number of multipath induced peaks. The Np peaks are then used to realign and scale the input data before summation. TheRAKE 364 in effect has performed the phase-delay compensation usually done in beam-steering. The advantages of this approach compared to conventional beam steering techniques include that it is independent of antenna array geometries and steering vectors, it does not require iterative searches for directions as in LMS and its variants, and it is computationally very efficient. This approach is discussed in detail in copending application having Ser. No. 08/916,884, and filed on Aug. 21, 1997. - 122. While various embodiments of the present invention have been described in detail, it is apparent that modifications and adaptations of those embodiments will occur to those skilled in the art. However, it is to be expressly understood that such modifications and adaptations are within the scope of the present invention, as set forth in the following claims.
Claims (37)
1. A method for acquiring a signal having a bandwidth, comprising:
decomposing the signal into a plurality of signal segments, each signal segment having a signal segment bandwidth that is less than the signal bandwidth;
processing each of the signal segments to form a plurality of processed signal segments; and
combining the processed signal segments into a composite signal wherein the signal is one of analog or digital and the composite signal is the other one of analog or digital.
2. The method of , wherein the processing step includes performing analog-to-digital conversion of each of the signal segments.
claim 1
3. The method of , wherein the processing step includes performing digital-to-analog conversion of each of the signal segments.
claim 1
4. The method of , wherein the processing step includes removing a noise component from each of the signal segments to form a corresponding plurality of noise reduced signal segments and thereafter converting each of the noise reduced signal segments from one of analog or digital format to the other of analog or digital format.
claim 1
5. The method of , wherein in the processing step each of the signal segments is processed separately.
claim 1
6. The method of , wherein the composite signal has the same bandwidth as the signal bandwidth.
claim 1
7. The method of , wherein the composite signal is a time delayed replica of the signal.
claim 1
8. The method of , wherein the signal has a bandwidth of at least about 1 GHz.
claim 1
9. The method of , wherein the sum of the plurality of signal bandwidths is equivalent to the signal bandwidth.
claim 1
10. The method of , wherein the signal is in one of analog or digital format and the composite signal is in the other of analog or digital format.
claim 1
11. The method of , wherein the processing step comprises:
claim 1
assigning boundary values to a plurality of bins;
sampling a signal segment to provide a sampled value corresponding to the sampled portion of the signal segment;
comparing the sampled value with assigned boundary values for each of the plurality of bins;
selecting an appropriate bin for the sampled portion of the signal segment;
thereafter reassigning new boundary values to at least a portion of the plurality of bins; and
repeating the assigning, sampling, comparing and selecting steps.
12. The method of , wherein the processing step comprises:
claim 1
correlating the plurality of signal segments with a corresponding plurality of replicated signal segments to provide a corresponding plurality of correlation functions.
13. The method of , wherein the processing step comprises:
claim 12
determining an amplitude, time delay, and phase delay for at least a portion of a plurality of peaks defined by the plurality of correlation functions and
realigning and scaling at least a portion of the signal defined by the signal segments based on one or more of the amplitude, time delay, and phase delay for the at least a portion of the plurality of peaks.
14. An apparatus for acquiring a signal having a signal bandwidth, comprising:
means for receiving a signal in the form pseudorandom or random waveform having a signal bandwidth;
means for decomposing the signal into a plurality of signal segments, each signal segment having a signal segment bandwidth that is less than the signal bandwidth;
means for processing each of the signal segments to form a plurality of processed signal segments; and
means for combining the processed signal segments into a composite signal wherein the signal is one of analog or digital and the composite signal is the other one of analog or digital.
15. The apparatus of , wherein the means for processing includes means for performing analog-to-digital conversion of each of the signal segments.
claim 14
16. The apparatus of , wherein the means for processing includes means for performing digital-to-analog conversion of each of the signal segments.
claim 14
17. The apparatus of , wherein the means for decomposing is a plurality of low pass filters.
claim 14
18. The apparatus of , wherein the means for decomposing includes a plurality of analysis filters and the means for combining includes a plurality of synthesis filters.
claim 14
19. The apparatus of , wherein the means for combining is a perfect reconstruction filter bank.
claim 14
20. The apparatus of , wherein the means for processing includes at least one of a plurality of analog-to-digital converters and a plurality of digital-to-analog converters.
claim 14
21. The apparatus of , wherein the means for processing includes a noise rejecting quantizer.
claim 14
22. A method for reducing noise in a signal having a bandwidth, comprising:
decomposing the signal into a plurality of signal segments, each signal segment having a bandwidth that is less than the bandwidth of the signal and
removing a noise component from each of the signal segments to form a corresponding plurality of processed signal segments.
23. The method of , further comprising:
claim 22
combining each of the processed signal segments to form a composite signal.
24. The method of , wherein the composite signal has the same bandwidth as the signal.
claim 23
25. A system for reducing noise in a signal having a bandwidth, comprising:
means for decomposing the signal into a plurality of signal segments, each signal segment having a bandwidth that is less than the bandwidth of the signal and
means for removing a noise component from each of the signal segments to form a corresponding plurality of processed signal segments.
26. The system of , further comprising:
claim 25
means for combining each of the processed signal segments to form a composite signal.
27. The system of , wherein the composite signal has the same bandwidth as the signal.
claim 26
28. A method for combining a plurality of signal segments having a signal bandwidth, to form a composite signal having a composite bandwidth, the frequency band of the composite signal including each of the signal segments, the method comprising:
performing synthesis filtering on each of the plurality of signal segments to form the composite signal.
29. The method of , further comprising:
claim 28
emitting the plurality of signal segments from a plurality of signal sources and
receiving each of the plurality of signal segments using a corresponding plurality of signal receptors.
30. The method of , further comprising:
claim 28
converting each of the signal segments from an analog format to a digital format.
31. A system for assembling a plurality of signal segments, each having a signal bandwidth to form a composite signal having a composite bandwidth that includes the frequency range of each of the signal segments, the system comprising:
means for performing synthesis filtering on each of the plurality of signal segments to form the composite signal.
32. The system of , further comprising:
claim 31
means for emitting the plurality of signal segments from a plurality of signal sources and
means for receiving each of the plurality of signal segments.
33. The system of , further comprising:
claim 31
means for converting each of the signal segments from an analog format to a digital format.
34. The system of , further comprising:
claim 31
a plurality of analysis filters to decompose a source signal into a plurality of decomposed signal segments;
a plurality of digital-to-analog conversion devices for converting the plurality of decomposed signal segments from digital into analog format to form a corresponding plurality of analog signal segments;
a plurality of amplifiers to form a corresponding plurality of signal segments;
a plurality of signal emitters for emitting the plurality of signal segments; and
a plurality of receptors for receiving the plurality of signal segments.
35. The system of , further comprising:
claim 31
a plurality of analysis filters to decompose a source signal into a plurality of decomposed signal segments;
a plurality of amplifiers to amplify the decomposed signal segments to form a corresponding plurality of signal segments;
a plurality of signal emitters for emitting the plurality of signal segments; and
a plurality of receptors for receiving the plurality of signal segments.
36. The system of , further comprising:
claim 31
a plurality of receptors for receiving a plurality of analog signal segments;
a plurality of analog-to-digital converters to convert the plurality of analog signal segments into the plurality of signal segments.
37. A method for processing an analog signal having a bandwidth, comprising:
decomposing the analog signal into a plurality of analog signal segments, each analog signal segment having a signal segment bandwidth that is less than the signal bandwidth and
processing each of the analog signal segments to form a plurality of processed analog signal segments; and
combining the processed analog signal segments into a composite signal.
Priority Applications (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US09/730,330 US6362760B2 (en) | 1997-08-21 | 2000-12-04 | Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms |
US09/995,207 US6549151B1 (en) | 1997-08-21 | 2001-11-26 | Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms |
Applications Claiming Priority (5)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US5622897P | 1997-08-21 | 1997-08-21 | |
US5645597P | 1997-08-21 | 1997-08-21 | |
US8703698P | 1998-05-28 | 1998-05-28 | |
US09/137,383 US6252535B1 (en) | 1997-08-21 | 1998-08-20 | Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms |
US09/730,330 US6362760B2 (en) | 1997-08-21 | 2000-12-04 | Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms |
Related Parent Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US09/137,383 Division US6252535B1 (en) | 1996-08-23 | 1998-08-20 | Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms |
Related Child Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US09/730,316 Continuation US6380879B2 (en) | 1997-08-21 | 2000-12-04 | Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms |
Publications (2)
Publication Number | Publication Date |
---|---|
US20010000216A1 true US20010000216A1 (en) | 2001-04-12 |
US6362760B2 US6362760B2 (en) | 2002-03-26 |
Family
ID=27368991
Family Applications (4)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US09/137,383 Expired - Lifetime US6252535B1 (en) | 1996-08-23 | 1998-08-20 | Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms |
US09/730,330 Expired - Lifetime US6362760B2 (en) | 1997-08-21 | 2000-12-04 | Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms |
US09/730,316 Expired - Lifetime US6380879B2 (en) | 1997-08-21 | 2000-12-04 | Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms |
US09/995,207 Expired - Lifetime US6549151B1 (en) | 1997-08-21 | 2001-11-26 | Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms |
Family Applications Before (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US09/137,383 Expired - Lifetime US6252535B1 (en) | 1996-08-23 | 1998-08-20 | Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms |
Family Applications After (2)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US09/730,316 Expired - Lifetime US6380879B2 (en) | 1997-08-21 | 2000-12-04 | Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms |
US09/995,207 Expired - Lifetime US6549151B1 (en) | 1997-08-21 | 2001-11-26 | Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms |
Country Status (4)
Country | Link |
---|---|
US (4) | US6252535B1 (en) |
AU (1) | AU9027798A (en) |
GB (1) | GB2343801B (en) |
WO (1) | WO1999009650A1 (en) |
Cited By (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20050021261A1 (en) * | 2003-07-02 | 2005-01-27 | Akira Nara | Wideband signal analyzer |
US20060020428A1 (en) * | 2002-12-03 | 2006-01-26 | Qinetiq Limited | Decorrelation of signals |
US20090141775A1 (en) * | 2005-02-25 | 2009-06-04 | Data Fusion Corporation | Mitigating interference in a signal |
US7652608B1 (en) * | 2003-04-07 | 2010-01-26 | Photonics Products, Inc. | Channelized analog-to-digital converter |
US20130194893A1 (en) * | 2012-01-31 | 2013-08-01 | Cggveritas Services Sa | Method and apparatus for processing seismic data |
US10281584B2 (en) * | 2013-06-05 | 2019-05-07 | Airbus Defence And Space Limited | Receiver and method for direct sequence spread spectrum signals |
US10931294B2 (en) * | 2019-07-12 | 2021-02-23 | Agency For Defense Development | Apparatus and method for measuring frequency of signal |
Families Citing this family (101)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6188776B1 (en) | 1996-05-21 | 2001-02-13 | Interval Research Corporation | Principle component analysis of images for the automatic location of control points |
WO1997044953A1 (en) * | 1996-05-21 | 1997-11-27 | Matsushita Electric Industrial Co., Ltd. | Video and audio signal processor and audio signal processor |
US6947474B2 (en) | 1996-08-23 | 2005-09-20 | Tensorcomm, Inc. | Rake receiver for spread spectrum signal demodulation |
EP0999708A1 (en) * | 1998-11-06 | 2000-05-10 | TELEFONAKTIEBOLAGET L M ERICSSON (publ) | Channel error correction apparatus and method |
AU4278600A (en) | 1999-04-27 | 2000-11-10 | Brian De Champlain | Single receiver wireless tracking system |
US6683567B2 (en) * | 2000-07-18 | 2004-01-27 | Brian De Champlain | Single receiver wireless tracking system |
FR2799073B1 (en) * | 1999-09-29 | 2002-01-18 | France Telecom | METHOD FOR TRANSMITTING A BFDM / OQAM SIGNAL, CORRESPONDING MODULATION AND DEMODULATION METHODS AND DEVICE |
US6466615B1 (en) * | 1999-12-30 | 2002-10-15 | Intel Corporation | Delay locked loop based circuit for data communication |
US6741650B1 (en) * | 2000-03-02 | 2004-05-25 | Adc Telecommunications, Inc. | Architecture for intermediate frequency encoder |
KR100505510B1 (en) * | 2000-04-19 | 2005-08-04 | 주식회사 디지트리얼테크놀로지 | A Method of Region Adaptive Subband Image Coding |
US6392588B1 (en) * | 2000-05-03 | 2002-05-21 | Ramot University Authority For Applied Research & Industrial Development Ltd. | Multifrequency signal structure for radar systems |
US7146176B2 (en) | 2000-06-13 | 2006-12-05 | Shared Spectrum Company | System and method for reuse of communications spectrum for fixed and mobile applications with efficient method to mitigate interference |
DE10028593C1 (en) * | 2000-06-14 | 2001-10-18 | Daimler Chrysler Ag | Digital/analogue signal conversion method uses transformation with orthogonal functions and determination of coefficients for re-conversion into analogue range |
EP1307709B1 (en) * | 2000-08-02 | 2009-04-15 | Continental Teves AG & Co. oHG | Active magnetic field sensor, use thereof, method and device |
US7076164B2 (en) * | 2001-06-22 | 2006-07-11 | Tellabs Operations, Inc. | System and method for measuring power of optical signals carried over a fiber optic link |
US20030033611A1 (en) * | 2001-08-09 | 2003-02-13 | Shapiro Jerome M. | Embedded information modulation and demodulation using spectrum control orthogonal filter banks |
GB2396985B (en) | 2001-09-12 | 2005-05-11 | Data Fusion Corp | Gps near-far resistant receiver |
US20030058148A1 (en) * | 2001-09-21 | 2003-03-27 | Sheen Timothy W. | Multiple a-to-d converter scheme employing digital crossover filter |
US7158559B2 (en) | 2002-01-15 | 2007-01-02 | Tensor Comm, Inc. | Serial cancellation receiver design for a coded signal processing engine |
US8085889B1 (en) | 2005-04-11 | 2011-12-27 | Rambus Inc. | Methods for managing alignment and latency in interference cancellation |
US7394879B2 (en) * | 2001-11-19 | 2008-07-01 | Tensorcomm, Inc. | Systems and methods for parallel signal cancellation |
US7260506B2 (en) * | 2001-11-19 | 2007-08-21 | Tensorcomm, Inc. | Orthogonalization and directional filtering |
US20040146093A1 (en) * | 2002-10-31 | 2004-07-29 | Olson Eric S. | Systems and methods for reducing interference in CDMA systems |
US20050101277A1 (en) * | 2001-11-19 | 2005-05-12 | Narayan Anand P. | Gain control for interference cancellation |
US7787518B2 (en) * | 2002-09-23 | 2010-08-31 | Rambus Inc. | Method and apparatus for selectively applying interference cancellation in spread spectrum systems |
US7580448B2 (en) * | 2002-10-15 | 2009-08-25 | Tensorcomm, Inc | Method and apparatus for channel amplitude estimation and interference vector construction |
US6567030B1 (en) * | 2002-02-27 | 2003-05-20 | Lecroy Corporation | Sample synthesis for matching digitizers in interleaved systems |
US6653959B1 (en) * | 2002-05-22 | 2003-11-25 | Massachusetts Institute Of Technology | High dynamic range analog-to-digital converter having parallel equalizers |
US20030235252A1 (en) * | 2002-06-19 | 2003-12-25 | Jose Tellado | Method and system of biasing a timing phase estimate of data segments of a received signal |
GB0214621D0 (en) * | 2002-06-25 | 2002-08-07 | Koninkl Philips Electronics Nv | Signal receiver |
US20040208238A1 (en) * | 2002-06-25 | 2004-10-21 | Thomas John K. | Systems and methods for location estimation in spread spectrum communication systems |
US6792057B2 (en) * | 2002-08-29 | 2004-09-14 | Bae Systems Information And Electronic Systems Integration Inc | Partial band reconstruction of frequency channelized filters |
US7577186B2 (en) * | 2002-09-20 | 2009-08-18 | Tensorcomm, Inc | Interference matrix construction |
US8761321B2 (en) * | 2005-04-07 | 2014-06-24 | Iii Holdings 1, Llc | Optimal feedback weighting for soft-decision cancellers |
US7463609B2 (en) * | 2005-07-29 | 2008-12-09 | Tensorcomm, Inc | Interference cancellation within wireless transceivers |
US7876810B2 (en) * | 2005-04-07 | 2011-01-25 | Rambus Inc. | Soft weighted interference cancellation for CDMA systems |
US7787572B2 (en) | 2005-04-07 | 2010-08-31 | Rambus Inc. | Advanced signal processors for interference cancellation in baseband receivers |
US7808937B2 (en) | 2005-04-07 | 2010-10-05 | Rambus, Inc. | Variable interference cancellation technology for CDMA systems |
US20050180364A1 (en) * | 2002-09-20 | 2005-08-18 | Vijay Nagarajan | Construction of projection operators for interference cancellation |
US8005128B1 (en) | 2003-09-23 | 2011-08-23 | Rambus Inc. | Methods for estimation and interference cancellation for signal processing |
US20050123080A1 (en) * | 2002-11-15 | 2005-06-09 | Narayan Anand P. | Systems and methods for serial cancellation |
US8179946B2 (en) | 2003-09-23 | 2012-05-15 | Rambus Inc. | Systems and methods for control of advanced receivers |
AU2003301493A1 (en) * | 2002-10-15 | 2004-05-04 | Tensorcomm Inc. | Method and apparatus for interference suppression with efficient matrix inversion in a ds-cdma system |
US7219037B2 (en) | 2002-10-24 | 2007-05-15 | Lecroy Corporation | High bandwidth oscilloscope |
EP1554807B1 (en) * | 2002-10-24 | 2010-10-06 | Lecroy Corporation | High bandwidth real time oscilloscope |
US7711510B2 (en) | 2002-10-24 | 2010-05-04 | Lecroy Corporation | Method of crossover region phase correction when summing signals in multiple frequency bands |
US7957938B2 (en) * | 2002-10-24 | 2011-06-07 | Lecroy Corporation | Method and apparatus for a high bandwidth oscilloscope utilizing multiple channel digital bandwidth interleaving |
US10659071B2 (en) | 2002-10-24 | 2020-05-19 | Teledyne Lecroy, Inc. | High bandwidth oscilloscope |
US7541959B1 (en) * | 2003-04-07 | 2009-06-02 | Photonics Products, Inc. | High speed signal processor |
US7324036B2 (en) * | 2003-05-12 | 2008-01-29 | Hrl Laboratories, Llc | Adaptive, intelligent transform-based analog to information converter method and system |
US7409010B2 (en) * | 2003-06-10 | 2008-08-05 | Shared Spectrum Company | Method and system for transmitting signals with reduced spurious emissions |
US7457350B2 (en) * | 2003-07-18 | 2008-11-25 | Artimi Ltd. | Communications systems and methods |
US20050031021A1 (en) * | 2003-07-18 | 2005-02-10 | David Baker | Communications systems and methods |
US20050050130A1 (en) * | 2003-09-02 | 2005-03-03 | Dabak Anand G. | Ranging in multi-band OFDM communications systems |
US7400692B2 (en) * | 2004-01-14 | 2008-07-15 | Interdigital Technology Corporation | Telescoping window based equalization |
US7477710B2 (en) * | 2004-01-23 | 2009-01-13 | Tensorcomm, Inc | Systems and methods for analog to digital conversion with a signal cancellation system of a receiver |
US20050169354A1 (en) * | 2004-01-23 | 2005-08-04 | Olson Eric S. | Systems and methods for searching interference canceled data |
US7460839B2 (en) | 2004-07-19 | 2008-12-02 | Purewave Networks, Inc. | Non-simultaneous frequency diversity in radio communication systems |
US7263335B2 (en) * | 2004-07-19 | 2007-08-28 | Purewave Networks, Inc. | Multi-connection, non-simultaneous frequency diversity in radio communication systems |
US7253761B1 (en) * | 2004-11-08 | 2007-08-07 | United States Of America As Represented By The Secretary Of The Army | Analog to digital conversion with signal expansion |
US20060125689A1 (en) * | 2004-12-10 | 2006-06-15 | Narayan Anand P | Interference cancellation in a receive diversity system |
US20060229051A1 (en) * | 2005-04-07 | 2006-10-12 | Narayan Anand P | Interference selection and cancellation for CDMA communications |
US7826516B2 (en) | 2005-11-15 | 2010-11-02 | Rambus Inc. | Iterative interference canceller for wireless multiple-access systems with multiple receive antennas |
US20060267811A1 (en) * | 2005-05-24 | 2006-11-30 | Kan Tan | Method and apparatus for reconstructing signals from sub-band signals |
KR101184323B1 (en) * | 2005-11-03 | 2012-09-19 | 삼성전자주식회사 | Analog to digital conversion method and apparatus of receiver supporting software defined multi-standard radios |
US7345629B2 (en) * | 2006-02-21 | 2008-03-18 | Northrop Grumman Corporation | Wideband active phased array antenna system |
US8997170B2 (en) | 2006-12-29 | 2015-03-31 | Shared Spectrum Company | Method and device for policy-based control of radio |
US8027249B2 (en) | 2006-10-18 | 2011-09-27 | Shared Spectrum Company | Methods for using a detector to monitor and detect channel occupancy |
US7564816B2 (en) * | 2006-05-12 | 2009-07-21 | Shared Spectrum Company | Method and system for determining spectrum availability within a network |
US8055204B2 (en) | 2007-08-15 | 2011-11-08 | Shared Spectrum Company | Methods for detecting and classifying signals transmitted over a radio frequency spectrum |
US8326313B2 (en) * | 2006-05-12 | 2012-12-04 | Shared Spectrum Company | Method and system for dynamic spectrum access using detection periods |
US8155649B2 (en) * | 2006-05-12 | 2012-04-10 | Shared Spectrum Company | Method and system for classifying communication signals in a dynamic spectrum access system |
US9538388B2 (en) | 2006-05-12 | 2017-01-03 | Shared Spectrum Company | Method and system for dynamic spectrum access |
US8184653B2 (en) | 2007-08-15 | 2012-05-22 | Shared Spectrum Company | Systems and methods for a cognitive radio having adaptable characteristics |
US7304597B1 (en) * | 2006-05-26 | 2007-12-04 | Lecroy Corporation | Adaptive interpolation for use in reducing signal spurs |
US7633417B1 (en) * | 2006-06-03 | 2009-12-15 | Alcatel Lucent | Device and method for enhancing the human perceptual quality of a multimedia signal |
EP3985873A1 (en) * | 2006-07-04 | 2022-04-20 | Dolby International AB | Filter system comprising a filter converter and a filter compressor and method for operating the filter system |
DE502007005695D1 (en) * | 2006-08-01 | 2010-12-30 | Continental Teves Ag & Co Ohg | SENSOR ARRANGEMENT FOR PRECISELY RECORDING RELATIVE MOVEMENTS BETWEEN AN ENCODER AND A SENSOR |
US7474972B2 (en) * | 2007-03-23 | 2009-01-06 | Tektronix, Inc. | Bandwidth multiplication for a test and measurement instrument using non-periodic functions for mixing |
US8090052B2 (en) * | 2007-03-29 | 2012-01-03 | Intel Corporation | Systems and methods for digital delayed array transmitter architecture with beam steering capability for high data rate |
WO2008145800A1 (en) | 2007-05-25 | 2008-12-04 | Nokia Corporation | Interference mitigation |
US7535394B2 (en) * | 2007-07-10 | 2009-05-19 | Lecroy Corporation | High speed arbitrary waveform generator |
GB2452309A (en) * | 2007-08-31 | 2009-03-04 | Agilent Technologies Inc | Circuit for sample rate conversion |
EP2319260A2 (en) * | 2008-08-19 | 2011-05-11 | Shared Spectrum Company | Method and system for dynamic spectrum access using specialty detectors and improved networking |
EP2369362A1 (en) * | 2010-03-18 | 2011-09-28 | Siemens Milltronics Process Instruments Inc. | A receiver for a pulse-echo ranging system with digital polyphase decimation filter |
TWI440312B (en) * | 2010-11-15 | 2014-06-01 | Anpec Electronics Corp | Functional device for analog-to-digital converting |
FR2968149B1 (en) * | 2010-11-30 | 2013-03-15 | Thales Sa | METHOD AND SYSTEM FOR ADAPTIVE HF BAND COMMUNICATIONS |
US8406340B2 (en) * | 2011-01-14 | 2013-03-26 | Broadcom Corporation | Distortion and aliasing reduction for digital to analog conversion |
US8659453B1 (en) * | 2011-04-07 | 2014-02-25 | Lockheed Martin Corporation | Digital radio frequency memory utilizing time interleaved analog to digital converters and time interleaved digital to analog converters |
US9432042B2 (en) | 2011-05-26 | 2016-08-30 | Tektronix, Inc. | Test and measurement instrument including asynchronous time-interleaved digitizer using harmonic mixing |
US9568503B2 (en) | 2011-05-26 | 2017-02-14 | Tektronix, Inc. | Calibration for test and measurement instrument including asynchronous time-interleaved digitizer using harmonic mixing |
US8742749B2 (en) | 2011-05-26 | 2014-06-03 | Tektronix, Inc. | Test and measurement instrument including asynchronous time-interleaved digitizer using harmonic mixing |
US9306590B2 (en) | 2011-05-26 | 2016-04-05 | Tektronix, Inc. | Test and measurement instrument including asynchronous time-interleaved digitizer using harmonic mixing |
US8781023B2 (en) * | 2011-11-01 | 2014-07-15 | At&T Intellectual Property I, L.P. | Method and apparatus for improving transmission of data on a bandwidth expanded channel |
US8774308B2 (en) * | 2011-11-01 | 2014-07-08 | At&T Intellectual Property I, L.P. | Method and apparatus for improving transmission of data on a bandwidth mismatched channel |
US20140163940A1 (en) * | 2012-12-11 | 2014-06-12 | David E. Erisman | Method and system for modeling rf emissions occurring in a radio frequency band |
DE102012025319B4 (en) * | 2012-12-22 | 2019-10-10 | Diehl Defence Gmbh & Co. Kg | A method for processing a navigation satellite signal and receiver for a navigation satellite signal |
US8928514B1 (en) | 2013-09-13 | 2015-01-06 | Tektronix, Inc. | Harmonic time domain interleave to extend oscilloscope bandwidth and sample rate |
CN107748354B (en) * | 2017-08-08 | 2021-11-30 | 中国电子科技集团公司第三十八研究所 | Broadband digital beam forming device based on analysis and synthesis |
CN108933598A (en) * | 2018-06-19 | 2018-12-04 | 广州视源电子科技股份有限公司 | Digital sample filtering method, device and readable storage medium storing program for executing |
US11469876B1 (en) * | 2020-09-25 | 2022-10-11 | Raytheon Company | Trigger to data synchronization of gigahertz digital-to-analog converters |
Family Cites Families (57)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE610989C (en) | 1930-07-01 | 1935-03-20 | Gewerkschaft Wallram | Chisel with hard metal insert |
DE558910C (en) | 1931-02-06 | 1932-09-13 | Beloit Iron Works | Device for winding up paper webs |
US4359738A (en) | 1974-11-25 | 1982-11-16 | The United States Of America As Represented By The Secretary Of The Navy | Clutter and multipath suppressing sidelobe canceller antenna system |
US5412391A (en) | 1977-10-06 | 1995-05-02 | The United States Of America As Represented By The Secretary Of The Navy | Adaptive decorrelating sidelobe canceller |
US4665401A (en) * | 1980-10-10 | 1987-05-12 | Sperry Corporation | Millimeter wave length guidance system |
IL67379A (en) | 1982-12-01 | 1985-11-29 | Tadiran Israel Elect Ind Ltd | Real-time frequency management system for hf communication networks |
US4893316A (en) | 1985-04-04 | 1990-01-09 | Motorola, Inc. | Digital radio frequency receiver |
US4965732A (en) | 1985-11-06 | 1990-10-23 | The Board Of Trustees Of The Leland Stanford Junior University | Methods and arrangements for signal reception and parameter estimation |
DE3687748T2 (en) | 1985-12-26 | 1993-05-27 | Matsushita Electric Ind Co Ltd | TRANSMISSION METHOD OF A DIGITAL SIGNAL WITH IMPROVED ERROR RATE PROPERTIES FOR MULTIPLE-WAY TRANSMISSION. |
US4694467A (en) | 1986-07-03 | 1987-09-15 | Signatron, Inc. | Modem for use in multipath communication systems |
FR2606237B1 (en) | 1986-10-31 | 1988-12-09 | Trt Telecom Radio Electr | ANALOG CRYPTOPHONY DEVICE WITH DYNAMIC BAND PERMUTATIONS |
US4737713A (en) * | 1986-11-26 | 1988-04-12 | Fonar Corporation | Apparatus and method for processing an electrical signal and increasing a signal-to-noise ratio thereof |
US4922506A (en) | 1988-01-11 | 1990-05-01 | Sicom Corporation | Compensating for distortion in a communication channel |
US4933639A (en) | 1989-02-13 | 1990-06-12 | The Board Of Regents, The University Of Texas System | Axis translator for magnetic resonance imaging |
US5109390A (en) | 1989-11-07 | 1992-04-28 | Qualcomm Incorporated | Diversity receiver in a cdma cellular telephone system |
US5119401A (en) | 1989-11-17 | 1992-06-02 | Nec Corporation | Decision feedback equalizer including forward part whose signal reference point is shiftable depending on channel response |
EP0459383A3 (en) | 1990-05-30 | 1993-12-15 | Pioneer Electronic Corp | Radio receiver |
US5099493A (en) | 1990-08-27 | 1992-03-24 | Zeger-Abrams Incorporated | Multiple signal receiver for direct sequence, code division multiple access, spread spectrum signals |
JPH04123621A (en) * | 1990-09-14 | 1992-04-23 | Nippon Telegr & Teleph Corp <Ntt> | Echo eraser |
JP2906646B2 (en) * | 1990-11-09 | 1999-06-21 | 松下電器産業株式会社 | Voice band division coding device |
US5390207A (en) | 1990-11-28 | 1995-02-14 | Novatel Communications Ltd. | Pseudorandom noise ranging receiver which compensates for multipath distortion by dynamically adjusting the time delay spacing between early and late correlators |
US5513176A (en) | 1990-12-07 | 1996-04-30 | Qualcomm Incorporated | Dual distributed antenna system |
IL100213A (en) | 1990-12-07 | 1995-03-30 | Qualcomm Inc | CDMA microcellular telephone system and distributed antenna system therefor |
US5218619A (en) | 1990-12-17 | 1993-06-08 | Ericsson Ge Mobile Communications Holding, Inc. | CDMA subtractive demodulation |
US5151919A (en) | 1990-12-17 | 1992-09-29 | Ericsson-Ge Mobile Communications Holding Inc. | Cdma subtractive demodulation |
US5561667A (en) * | 1991-06-21 | 1996-10-01 | Gerlach; Karl R. | Systolic multiple channel band-partitioned noise canceller |
US5355533A (en) | 1991-12-11 | 1994-10-11 | Xetron Corporation | Method and circuit for radio frequency signal detection and interference suppression |
US5263191A (en) | 1991-12-11 | 1993-11-16 | Westinghouse Electric Corp. | Method and circuit for processing and filtering signals |
US5515378A (en) | 1991-12-12 | 1996-05-07 | Arraycomm, Inc. | Spatial division multiple access wireless communication systems |
DE4201439A1 (en) | 1992-01-21 | 1993-07-22 | Daimler Benz Ag | High-rate data transmission procedure via digital radio channel - providing multipath propagation compensation by decision feedback equaliser of correctly phased and weighted antenna signal combination |
CA2088082C (en) * | 1992-02-07 | 1999-01-19 | John Hartung | Dynamic bit allocation for three-dimensional subband video coding |
JPH05268128A (en) | 1992-03-18 | 1993-10-15 | Kokusai Denshin Denwa Co Ltd <Kdd> | Cdma communication system |
US5237586A (en) | 1992-03-25 | 1993-08-17 | Ericsson-Ge Mobile Communications Holding, Inc. | Rake receiver with selective ray combining |
GB2268364B (en) * | 1992-06-25 | 1995-10-11 | Roke Manor Research | Improvements in or relating to radio communication systems |
US5224122A (en) | 1992-06-29 | 1993-06-29 | Motorola, Inc. | Method and apparatus for canceling spread-spectrum noise |
JP2689823B2 (en) | 1992-07-21 | 1997-12-10 | 松下電器産業株式会社 | Image signal reproducing device and disc device |
US5289499A (en) | 1992-12-29 | 1994-02-22 | At&T Bell Laboratories | Diversity for direct-sequence spread spectrum systems |
JP3143247B2 (en) | 1993-01-11 | 2001-03-07 | 沖電気工業株式会社 | Code division multiple access demodulator |
JPH0744473B2 (en) | 1993-02-02 | 1995-05-15 | 日本電気株式会社 | Demodulation system |
US5353302A (en) | 1993-02-03 | 1994-10-04 | At&T Bell Laboratories | Signal despreader for CDMA systems |
US5305349A (en) | 1993-04-29 | 1994-04-19 | Ericsson Ge Mobile Communications Inc. | Quantized coherent rake receiver |
US5437055A (en) | 1993-06-03 | 1995-07-25 | Qualcomm Incorporated | Antenna system for multipath diversity in an indoor microcellular communication system |
US5442627A (en) | 1993-06-24 | 1995-08-15 | Qualcomm Incorporated | Noncoherent receiver employing a dual-maxima metric generation process |
GB9315845D0 (en) | 1993-07-30 | 1993-09-15 | Roke Manor Research | Apparatus for use in equipment providing a digital radio link between a fixed and a mobile radio unit |
DE4326843C2 (en) | 1993-08-10 | 1997-11-20 | Hirschmann Richard Gmbh Co | Receiving method and receiving antenna system for eliminating reusable interference or control device for performing this method |
JPH0774687A (en) | 1993-09-03 | 1995-03-17 | Kokusai Denshin Denwa Co Ltd <Kdd> | Diversity system |
US5481570A (en) | 1993-10-20 | 1996-01-02 | At&T Corp. | Block radio and adaptive arrays for wireless systems |
US5386202A (en) | 1993-11-03 | 1995-01-31 | Sicom, Inc. | Data communication modulation with managed intersymbol interference |
DE4343959C2 (en) | 1993-12-22 | 1996-04-25 | Hirschmann Richard Gmbh Co | Receiving method and receiving antenna system for eliminating reusable interference or control device for performing this method |
US5553098A (en) | 1994-04-12 | 1996-09-03 | Sicom, Inc. | Demodulator with selectable coherent and differential data |
US5440265A (en) | 1994-09-14 | 1995-08-08 | Sicom, Inc. | Differential/coherent digital demodulator operating at multiple symbol points |
US5568142A (en) | 1994-10-20 | 1996-10-22 | Massachusetts Institute Of Technology | Hybrid filter bank analog/digital converter |
US5602833A (en) | 1994-12-19 | 1997-02-11 | Qualcomm Incorporated | Method and apparatus for using Walsh shift keying in a spread spectrum communication system |
US5566167A (en) * | 1995-01-04 | 1996-10-15 | Lucent Technologies Inc. | Subband echo canceler |
US5561668A (en) * | 1995-07-06 | 1996-10-01 | Coherent Communications Systems Corp. | Echo canceler with subband attenuation and noise injection control |
US6430216B1 (en) * | 1997-08-22 | 2002-08-06 | Data Fusion Corporation | Rake receiver for spread spectrum signal demodulation |
US6177893B1 (en) | 1998-09-15 | 2001-01-23 | Scott R. Velazquez | Parallel processing analog and digital converter |
-
1998
- 1998-08-20 GB GB0002745A patent/GB2343801B/en not_active Expired - Fee Related
- 1998-08-20 AU AU90277/98A patent/AU9027798A/en not_active Abandoned
- 1998-08-20 WO PCT/US1998/017278 patent/WO1999009650A1/en active Application Filing
- 1998-08-20 US US09/137,383 patent/US6252535B1/en not_active Expired - Lifetime
-
2000
- 2000-12-04 US US09/730,330 patent/US6362760B2/en not_active Expired - Lifetime
- 2000-12-04 US US09/730,316 patent/US6380879B2/en not_active Expired - Lifetime
-
2001
- 2001-11-26 US US09/995,207 patent/US6549151B1/en not_active Expired - Lifetime
Cited By (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20060020428A1 (en) * | 2002-12-03 | 2006-01-26 | Qinetiq Limited | Decorrelation of signals |
US7299161B2 (en) * | 2002-12-03 | 2007-11-20 | Qinetiq Limited | Decorrelation of signals |
US7652608B1 (en) * | 2003-04-07 | 2010-01-26 | Photonics Products, Inc. | Channelized analog-to-digital converter |
US20050021261A1 (en) * | 2003-07-02 | 2005-01-27 | Akira Nara | Wideband signal analyzer |
US7428464B2 (en) * | 2003-07-02 | 2008-09-23 | Tektronix, Inc. | Wideband signal analyzer |
US20090141775A1 (en) * | 2005-02-25 | 2009-06-04 | Data Fusion Corporation | Mitigating interference in a signal |
US7626542B2 (en) | 2005-02-25 | 2009-12-01 | Data Fusion Corporation | Mitigating interference in a signal |
US20130194893A1 (en) * | 2012-01-31 | 2013-08-01 | Cggveritas Services Sa | Method and apparatus for processing seismic data |
US9360577B2 (en) * | 2012-01-31 | 2016-06-07 | Cgg Services Sa | Method and apparatus for processing seismic data |
US10281584B2 (en) * | 2013-06-05 | 2019-05-07 | Airbus Defence And Space Limited | Receiver and method for direct sequence spread spectrum signals |
US10931294B2 (en) * | 2019-07-12 | 2021-02-23 | Agency For Defense Development | Apparatus and method for measuring frequency of signal |
Also Published As
Publication number | Publication date |
---|---|
GB0002745D0 (en) | 2000-03-29 |
AU9027798A (en) | 1999-03-08 |
US6252535B1 (en) | 2001-06-26 |
GB2343801A (en) | 2000-05-17 |
US20010000660A1 (en) | 2001-05-03 |
US6549151B1 (en) | 2003-04-15 |
US6362760B2 (en) | 2002-03-26 |
WO1999009650A1 (en) | 1999-02-25 |
GB2343801B (en) | 2001-09-12 |
US6380879B2 (en) | 2002-04-30 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US6252535B1 (en) | Method and apparatus for acquiring wide-band pseudorandom noise encoded waveforms | |
US6792057B2 (en) | Partial band reconstruction of frequency channelized filters | |
US7103537B2 (en) | System and method for linear prediction | |
JP2994752B2 (en) | CDMA subtractive demodulation | |
US6697633B1 (en) | Method permitting increased frequency re-use in a communication network, by recovery of transmitted information from multiple cochannel signals | |
US6788734B2 (en) | Rake receiver for spread spectrum signal demodulation | |
US6208295B1 (en) | Method for processing radio signals that are subject to unwanted change during propagation | |
US6085077A (en) | Hardware efficient digital channelized receiver | |
KR100506198B1 (en) | Multichannel digital receiver for global positioning system | |
Amin et al. | Subspace array processing for the suppression of FM jamming in GPS receivers | |
US6658234B1 (en) | Method for extending the effective dynamic range of a radio receiver system | |
KR20040066098A (en) | Interference cancellation in a signal | |
US8121222B2 (en) | Systems and methods for construction of time-frequency surfaces and detection of signals | |
CN111095015B (en) | Method and system for detecting an object by a passive radar system utilizing a per-carrier multi-channel illuminator source | |
KR20050044494A (en) | Construction of an interference matrix for a coded signal processing engine | |
CN1732634A (en) | A method and system for autocorrelation filtering | |
KR102183439B1 (en) | Method and apparatus for estimating direction of arrival using combined beamspace music and tma | |
US7242731B2 (en) | Method for synchronizing a receiver, a system, and an electronic device | |
CN109975842A (en) | A kind of blind catching method of Big Dipper satellite signal high-precision based on wavelet transformation | |
US6947474B2 (en) | Rake receiver for spread spectrum signal demodulation | |
US7027942B1 (en) | Multirate spectral analyzer with adjustable time-frequency resolution | |
CN103701515A (en) | Digital multi-beam forming method | |
EP1461633A1 (en) | Method and apparatus for signal receipt and acquisition | |
US6437733B1 (en) | Method of processing multipath navigation signals in a receiver having a plurality of antennas | |
US6384784B1 (en) | Direction finder system using spread spectrum techniques |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AS | Assignment |
Owner name: AIR FORCE, UNITED STATES, OHIO Free format text: CONFIRMATORY LICENSE;ASSIGNOR:DATA FUSION CORPORATION;REEL/FRAME:012077/0657 Effective date: 20010619 |
|
STCF | Information on status: patent grant |
Free format text: PATENTED CASE |
|
FPAY | Fee payment |
Year of fee payment: 4 |
|
FPAY | Fee payment |
Year of fee payment: 8 |
|
FPAY | Fee payment |
Year of fee payment: 12 |