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: 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: 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 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 adaptive signal processing system utilizes a pseudo-median cascaded canceller to compute a set of complex adaptive weights and generate a filtered output signal. The system includes a plurality of building blocks arranged in a Gram-Schmidt cascaded canceller-type configuration for sequentially decorrelating input signals from each other to thereby yield a single filtered output signal. Each building block includes a local main input channel which receives a local main input signal, a local auxiliary input channel which receives a local auxiliary input signal, and a local output channel which sends a local filtered output signal. Each building block generates a complex adaptive weight which is the sample median value of the real and imaginary parts of the ratio of local main input weight training data to local auxiliary input weight training data, and each building block generates a local output signal utilizing the complex adaptive weight.

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(?)={tilde over (x)}T(?)s+?(?); 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}, . . . , {circumflex over (x)}1{L?1}, {circumflex over (x)}1{l?1+(M?1)(N?1)}]; computing power estimates {circumflex over (?)}1(?)=|{circumflex over (x)}1(?)|? for ?=?(M?1)(N?1), . . . , L?1+(M?1)(N?1) and 0<??2; computing MMSE filters according to w(?)=?(?) (C(?)+R)?1 s, where ?(?)=E[|x(?)|?] is the power of x(?), for 0<??2, and R=E[?(?) ?H(?)] 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+?(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}, . . .

Abstract: An adaptive signal processing system utilizes a pseudo-median cascaded canceller to compute a set of complex adaptive weights and generate a filtered output signal. The system includes a plurality of building blocks arranged in a Gram-Schmidt cascaded canceller-type configuration for sequentially decorrelating input signals from each other to thereby yield a single filtered output signal. Each building block includes a local main input channel which receives a local main input signal, a local auxiliary input channel which receives a local auxiliary input signal, and a local output channel which sends a local filtered output signal. Each building block generates a complex adaptive weight which is the sample median value of the real and imaginary parts of the ratio of local main input weight training data to local auxiliary input weight training data, and each building block generates a local output signal utilizing the complex adaptive weight.

Abstract: A method for orthogonalizing inputs with respect to each other. The method omprises the steps of: generating a root structure of N inputs having input order 1 to N, where 2.sup.m-1 <N.ltoreq.2.sup.m and m is an integer .gtoreq.1; inverting the order of the root structure to generate an inverted root structure having input order N to 1; partially orthogonalizing the root structure and the inverted root structure in associated respective decorrelation circuits to remove inputs common to their first 2.sup.m-I inputs where I=1; splitting off two substructures from the root structure, where the first substructure has input order 1 to 2.sup.m-I and the second substructure has input order 2.sup.m-I to 1, where I=1; splitting off two substructures from the inverted root structure, where the first substructure has input order 2.sup.m to 2.sup.m-I and the second substructure has input order 2.sup.m-I to 2.sup.

Abstract: A stacking container to receive shaped parts (2), in particular stamped sheet metal parts, consists of a frame stand (3) with upper and lower holding ledges (6, 7) between which the shaped parts (2) are being held in the upright position. The holding edges (6, 7) comprise profile notches (9, 8) for the edges of the shaped parts (2). Adjacent to every upper holding ledge (10) a height adjustable safety ledge (10) is mounted; it also is equipped with profile notches (12). In their lower position the safety ledges (10) are holding the edges of the shaped parts (2) received, when the stacking container is being transported.

Abstract: An apparatus for nulling signals from unwanted interference sources. The aratus includes an N element antenna array interconnected with a weighted Butler matrix. The outputs of the Butler matrix are applied to an adaptive reducing matrix having outputs (x.sub.2, . . . ,x.sub.L), with L<N, where is the main antenna channel signal, x.sub.1, and (x.sub.2, . . . ,x.sub.L) are the signals required to null the effects of jammer signals received in the sidelobes of the main antenna channel. The signals (x.sub.1, . . . ,x.sub.L) are directed to the inputs of a sidelobe canceller.

Abstract: A radar doppler processor, comprising M, M=N-1, tap delay lines; N digital multipliers; a N-point fast fourier transform network; and a fast orthogonalizing network to orthogonalize each subband output signal to eliminate cross-correlations between all output signals.

Abstract: A space-time adaptive filter system is provided for eliminating unwanted signals from a radar or communication system. The filter system receives a main channel and several auxiliary channels wherein the target signal is not correlated between the various signal channels. Correlated noise components are eliminated by decorrelating the signals. The adaptive filter includes a Gram-Schmidt processor for sequentially decorrelating the auxiliary signals from the main signal. Each decorrelation element of the Gram-Schmidt processor comprises a transverse orthonormal ladder filter.