Abstract: Systems and method of detection and discrimination of targets in the presence of interference are disclosed. A system transmits a signal and then receives signals including interference and reflections of transmitted signals. The system processes the received signals and transmitted signals to generate a 2D representation of the STAP cube with one of the dimensions collapsed. The system then reduces the interference contributions and identifies angle and Doppler component of potential targets. The system then computes slices, which are one dimensional representation of cross-ambiguity functions of the received and transmitted signals. It reduces the interference contributions in the slices and determines range components of the targets.

Abstract: Systems and method of detection and discrimination of targets in the presence of interference are disclosed. A system transmits a signal and then receives signals including interference and reflections of transmitted signals. The system processes the received signals and transmitted signals to generate a 2D representation of the STAP cube with one of the dimensions collapsed. The system then reduces the interference contributions and identifies angle and Doppler component of potential targets. The system then computes slices, which are one dimensional representation of cross-ambiguity functions of the received and transmitted signals. It reduces the interference contributions in the slices and determines range components of the targets.

Abstract: A system and methods for multistep target detection and parameter estimation which utilizes slices and/or projections of the cross-ambiguity function of the transmitted and received signals of a sensor system is disclosed. The system and methods of the present invention offer a computationally efficient means of detecting targets while achieving a high probability of detection and a reduced false alarm rate. Detection and parameter estimation of targets is accomplished by generating hypotheses and then validating the generated hypotheses. The hypotheses are generated using slices and/or projections of cross-ambiguity functions of transmitted signals and reflections received from the targets without the need to compute the entire cross-ambiguity function. After hypotheses are generated they are validated by determining the amplitude of a cross-ambiguity function at the coordinates of the hypotheses and comparing the amplitude to a predetermined threshold.

Abstract: The present invention relates to active sensor applications, and more particularly is directed to efficient systems and methods for detection and tracking of one or more targets. The invention provides a method for receiving signals reflected from one or more targets, processing the received signals and the transmitted signal to compute two or more slices of the cross ambiguity function associated with the signals, and estimating the signal delay and the Doppler shit associated with the targets from the computed slices.