Abstract: Systems, methods, and computer-readable storage media for generating, transmitting, and utilizing a composite radar and communication waveform are disclosed. The composite radar and communication waveform may facilitate radar detection and data communication operations and may be generated from a frequency modulated (FM) radar waveform and a communication signal. In an aspect, the composite radar and communication waveform may be generated by iteratively executing a shaping process against the FM radar waveform and the communication signal until a first stop criterion is satisfied to produce an initial composite radar and communication waveform having the communication signal embedded therein, and then iteratively executing an enhancement process against the initial composite radar waveform and the communication signal until a second stop criterion is satisfied to produce a final composite radar and communication waveform suitable for both radar detection and data communication operations.

Abstract: The present application discloses a new form of ?-STAP, referred to herein as post ?-STAP or P?-STAP, which overcomes the drawbacks associated with existing ?-STAP techniques. The P?-STAP techniques described herein facilitate the generation of additional training data and homogenization after pulse compression. For example, P?-STAP techniques may apply a plurality of homogenization filters to a pulse compressed datacube generated from an input radar waveform, which produces a plurality of new pulse compressed datacubes with improved characteristics. Unlike existing ?-STAP techniques described above, which require pre-pulse compressed data to operate, the P?-STAP techniques disclosed in the present application are designed to utilize pulse compressed data, and therefore may be readily applied to legacy radar systems.

Abstract: An ad hoc approach denoted as devoid clutter capture and filling (DeCCaF) that addresses the nonstationarity effects that arise when input radar waveform returns exhibiting dynamic spectra variations are processed to combat dynamic RFI is disclosed. Portions of the spectra of each input waveform return of a set of input radar waveform returns processed during the CPI may be filled with clutter information borrowed from other waveform returns of the set of waveform returns. DeCCaF may combined with an appropriate filter (e.g., a matched filter, a mismatched filter) to achieve results that are nearly indistinguishable from input radar waveform returns in which no spectral variation are present.

Abstract: An ad hoc approach denoted as devoid clutter capture and filling (DeCCaF) that addresses the nonstationarity effects that arise when input radar waveform returns exhibiting dynamic spectra variations are processed to combat dynamic RFI is disclosed. Portions of the spectra of each input waveform return of a set of input radar waveform returns processed during the CPI may be filled with clutter information borrowed from other waveform returns of the set of waveform returns. DeCCaF may combined with an appropriate filter (e.g., a matched filter, a mismatched filter) to achieve results that are nearly indistinguishable from input radar waveform returns in which no spectral variation are present.

Abstract: The present application discloses a new form of ?-STAP, referred to herein as post ?-STAP or P?-STAP, which overcomes the drawbacks associated with existing ?-STAP techniques. The P?-STAP techniques described herein facilitate the generation of additional training data and homogenization after pulse compression. For example, P?-STAP techniques may apply a plurality of homogenization filters to a pulse compressed datacube generated from an input radar waveform, which produces a plurality of new pulse compressed datacubes with improved characteristics. Unlike existing ?-STAP techniques described above, which require prepulse compressed data to operate, the P?-STAP techniques disclosed in the present application are designed to utilize pulse compressed data, and therefore may be readily applied to legacy radar systems.

Abstract: Systems, methods, and computer-readable storage media for generating, transmitting, and utilizing a composite radar and communication waveform are disclosed. The composite radar and communication waveform may facilitate radar detection and data communication operations and may be generated from a frequency modulated (FM) radar waveform and a communication signal. In an aspect, the composite radar and communication waveform may be generated by iteratively executing a shaping process against the FM radar waveform and the communication signal until a first stop criterion is satisfied to produce an initial composite radar and communication waveform having the communication signal embedded therein, and then iteratively executing an enhancement process against the initial composite radar waveform and the communication signal until a second stop criterion is satisfied to produce a final composite radar and communication waveform suitable for both radar detection and data communication operations.

Abstract: Performing medical imaging. The generation of medical images, which includes a Source AFFine Image REconstruction (SAFFIRE) algorithm, is based on an iterative implementation of minimum mean-square error (MMSE) estimation within an affine-transformed solution space and utilizes a matched filter bank initialization coupled with energy normalization of each successive estimate. An incoherent integration technique provides an alternative implementation strategy to either increase signal-to-noise ratio (SNR) or generalize the estimator to accommodate temporally-separated interference sources. In addition, the estimator solution may be employed to determine volumetric constraints with which to re-apply the estimator to further improve the estimation accuracy.

Abstract: One aspect of this disclosure relates to a method for processing a received, modulated radar pulse to resolve a radar target from noise or other targets. According to an embodiment of the method, a radar return signal is received and samples of the radar return signal are obtained. A minimum mean-square error (MMSE) pulse compression filter is determined for each successive sample. The MMSE filter is separated into a number of components using contiguous blocking, where each component includes a piecewise MMSE pulse compression filter segment. An estimate of radar range profile is obtained from an initialization stage or a previous stage. The piecewise MMSE pulse compression filter segments are applied to improve accuracy of the estimate. The estimate is repeated for two or three stages to adaptively suppress range sidelobes to a level of a noise floor. Other aspects and embodiments are provided herein.

Abstract: Performing medical imaging. The generation of medical images, which includes a Source AFFine Image REconstruction (SAFFIRE) algorithm, is based on an iterative implementation of minimum mean-square error (MMSE) estimation within an affine-transformed solution space and utilizes a matched filter bank initialization coupled with energy normalization of each successive estimate. An incoherent integration technique provides an alternative implementation strategy to either increase signal-to-noise ratio (SNR) or generalize the estimator to accommodate temporally-separated interference sources. In addition, the estimator solution may be employed to determine volumetric constraints with which to re-apply the estimator to further improve the estimation accuracy.

Abstract: A single pulse imaging (SPI) radar system for creating a radar image from a plurality of Doppler phase-shifted return radar signals in a radar environment of moving targets includes a transmitter; a receiver for receiving a radar return signal; an analog-to-digital converter (ADC) coupled to the output of the receiver; a processor, coupled to the output of the ADC, that is programmed with an SPI algorithm that includes a bank of range/Doppler-dependent adaptive RMMSE-based filters; and a target detector. The algorithm estimates adaptively a range profile for each of the Doppler phase-shifted return radar signals to create the radar image of the moving targets.

Abstract: A radar receiver system includes a receiver, a processor, and a detector. The processor is programmed with a Multistatic Adaptive Pulse Compression (MAPC) algorithm for estimating adaptively a pulse compression filter, for each range cell of a plurality of range cells, and for each of a plurality of radar return signals, to remove interference between the radar return signals. MAPC may also include reiterative minimum mean-square error estimation for applying to each of the range cells in order to adaptively estimate a unique pulse compression filter for each cell. MAPC adaptively mitigates the masking problem that results from the autocorrelation of a waveform which produces range sidelobes scaled by the target amplitudes as well as the cross-correlation between waveforms. MAPC can also be applied when only 1 or some subset of the available illuminated radar range profiles are desired, with undesired information then discarded.

Abstract: A radar receiver system includes a receiver, a processor including a Doppler Compensated Adaptive Pulse Compressor (DCAPC) algorithm, possible other intermediate processing and a target detector. The DCAPC algorithm processes samples of a radar return signal, applies Minimum Mean Square Error (MMSE), or alternatively matched filtering, to the radar return signal to obtain initial radar impulse response estimates, computes power estimates, estimates a range cell Doppler shift for each range cell, computes range-dependent filters, applies the MMSE filters, and then repeats the cycle for subsequent reiterative stages until a desired length?L range window is reached, thereby resolving the scatterer from noise and other scatterers.

Abstract: A method and system for a device to embed a low signal to interference plus noise ratio (SINR) communications signal into the backscatter of an illuminating signal. The illuminating signal may be acoustic or electromagnetic (EM) such as radio frequency (RF), light, or infrared (IR). The embedded communications signal may be recovered at a desired receiver.

Abstract: A radar pulse compression repair (RPCR) system includes a receiver for receiving a radar return signal, a matched filter for applying matched filtering to the radar return signal to generate a matched filter output, a processor programmed for applying Radar Pulse Compression Repair (RPCR) to the matched filter output to suppress a plurality of range sidelobes from the matched filter output, and a detector for receiving the RPCR-processed output. The RPCR invention in operating upon the output of the matched filter enables RPCR to be employed as a post-processing stage in systems where it is not feasible to replace the existing pulse compression apparatus. RCPR can also be selectively employed when it is possible that large targets are present that may be masking smaller targets, thereby keeping computational complexity to a minimum.

Abstract: An apparatus for non-coherently detecting slow-moving targets in high resolution sea clutter includes a binary detector for converting high resolution radar returns, produced in response to a radar pulse scan of a plurality of identical pulses, into corresponding binary outputs based on a comparison of range cell magnitudes with a detector threshold. A range extent filter converts these binary outputs into an output indicating the presence or absence of a cluster of the returns that are closely spaced in range, while a third, persistence integration stage determines target range extent persistence over a predetermined time period. A detector stage declares detection of a target based on a comparison of the output of the third stage with a selected threshold.

Abstract: A method is provided for detecting a target signal of a specific known form in the presence of clutter. The method includes dividing a set of initial training data, derived from returns from a burst of identical pulses, into a set of censored data and a set of uncensored data. A covariance matrix estimate, based on the uncensored data, is used to compute adaptive coherence estimate values, and an average adaptive coherence estimate threshold level is computed for each Doppler band to obtain a corresponding threshold. The censored data and the covariance matrix estimate are used to compute adaptive coherence estimate values for the uncensored data for each Doppler band, and these values are compared with the respective thresholds to determine the presence or absence of the target signal.

Abstract: An adaptive radar processing system includes an antenna array for transmitting a radar signal and for receiving a return radar signal, and a signal processor programmed with an enhanced FRACTA algorithm (FRACTA.E). The basic FRACTA algorithm is enhanced to FRACTA.E with (any or all of) five enhancements, versions 1–5. Version 1 is a stopping criterion, for censoring samples, that is adaptive to a radar return data set. The inclusion of a stopping criterion improves the computational speed of FRACTA.E thereby improving its efficiency. Version 2 uses global censoring. Version 3 uses fast reiterative censoring. Version 4 uses segmenting of data vectors for AMF application. Version 5 uses Knowledge-aided covariance estimation (KACE) to reduce the required sample support that may be necessary in non-homogeneous environments, providing substantially the same level of detection performance with considerably less training data.

Abstract: A method for processing a received, modulated pulse (i.e. waveform) that requires predictive deconvolution to resolve a scatterer from noise and other scatterers includes receiving a return signal; obtaining L+(2M?1)(N?1) samples y of the return signal, where y(l)={tilde over (x)}T(l) s+v(l); applying RMMSE estimation to each successive N samples to obtain initial impulse response estimates [{circumflex over (x)}1{?(M?1)(N?1)}, . . . , {circumflex over (x)}1{?1}, {circumflex over (x)}1 {0}, . . . , {circumflex over (x)}1{L?1}, . . . , {circumflex over (x)}1{L}, {circumflex over (x)}1{?1 +(M?1)(N?1)}]; computing power estimates {circumflex over (?)}1(l)=|{circumflex over (x)}1(l)|? for l=?(M?1)(N?1), . . . , L?1+(M?1)(N?1) and 0<??2; computing MMSE filters according to w(l)=?(l) (C(l)+R)?1s, where ?(l)=E[|x(l)|?] is the power of x(l), for 0<??2, and R=E[v(l) vH(l)] is the noise covariance matrix; applying the MMSE filters to y to obtain [{circumflex over (x)}2{?(M?2)(N?1)}, . . .

Abstract: A method for processing a received, modulated pulse (i.e. waveform) that requires predictive deconvolution to resolve a scatterer from noise and other scatterers includes receiving a return signal; obtaining L+(2M?1)(N?1) samples y of the return signal, where y(l)={tilde over (x)}T(l)s+v(l); applying RMMSE estimation to each successive N samples to obtain initial impulse response estimates [{circumflex over (x)}1{?(M?1)(N?1)}, . . . , {circumflex over (x)}1{?1}, {circumflex over (x)}1{0}, . . . , {circumflex over (x)}1{L?1}, {circumflex over (x)}1{L}, . . . , {circumflex over (x)}1{L?1+(M?1)(N?1)}]; computing power estimates {circumflex over (?)}1(l)=|{circumflex over (x)}1(l)|2 for l=?(M?1)(N?1), . . . , L?1+(M?1)(N?1); computing MMSE filters according to w(l)=?(l)(C(l)+R)?1s, where ?(l)=|x(l)|2 is the power of x(l), and R=E[v(l)vH(l)] is the noise covariance matrix; applying the MMSE filters to y to obtain [{circumflex over (x)}2{?(M?2)(N?1)}, . . . , {circumflex over (x)}2{?1}, {circumflex over (x)}2{0}, .