Abstract: A system and method for target classification for an aircraft surveillance radar is provided. In one implementation, the track classifier provides tracks with an updated probability value based on its likelihood to conform to aircraft and non-aircraft target behavior. The track classifier identifies false tracks that may arise from weather and biological targets, and can detect aircrafts lacking Secondary Surveillance Radar (SSR) data. Various features and combinations of features are evaluated using a proposed clustering performance index (CPI) and used to discriminate between aircrafts and false tracks.

Abstract: A system and corresponding method for the concurrent operation of multiple radar systems on a common frequency and in the same geographical area includes a waveform generator that specifies certain operating parameters for the transmitted radar pulses. In a first instance, the carrier frequency can include an offset for each radar system. In a second instance, complementary codes can be used for the radar pulses such that each radar system operates with a unique code for substantially reducing the cross-talk between the radar systems. In another instance, both carrier frequency offset and complementary coded waveforms can be used to increase the number of radar systems that operate concurrently. Carrier frequency offset can also be used to combat range-wrap by using different carrier frequencies for adjacent radar pulses.

Abstract: This invention relates to a system and method for suppressing external interference in radar data provided by a plurality of sensors from a main sensor array, the data being pre-processed. The noise suppression system includes a first processing module and a second processing module. The first processing module receives the radar data and produces matched radar data while the second processing module receives the radar data and produces mis-matched radar data. The system further includes a beamformer that is in communication with the first processing module and an adaptive beamformer that is in communication with the second processing module and the beamformer. The beamformer receives the matched radar data and produces beamformed matched radar data.

Abstract: This invention relates to a spectral generator and a spectral generation method for receiving pre-processed range-doppler-sensor data and generating at least one noise-reduced high-resolution spectrum therefrom. The spectral generator comprises a window generator that generates a window which defines a plurality of range-doppler cells. The spectral generator further comprises a covariance matrix calculator that is in communication with the window generator to receive the range-doppler-sensor data within the window and calculate a covariance matrix estimate for a range-doppler cell of interest in the window. The spectral generator also includes a spectral calculator that is in communication with the covariance matrix calculator to calculate a high-resolution spectral vector based on a location matrix and a noise subspace matrix estimate.

Abstract: This invention relates to a spectral generator and a spectral generation method for receiving pre-processed range-doppler-sensor data and generating at least one noise-reduced high-resolution spectrum therefrom. The spectral generator comprises a window generator that generates a window which defines a plurality of range-doppler cells. The spectral generator further comprises a covariance matrix calculator that is in communication with the window generator to receive the range-doppler-sensor data within the window and calculate a covariance matrix estimate for a range-doppler cell of interest in the window. The spectral generator also includes a spectral calculator that is in communication with the covariance matrix calculator to calculate a high-resolution spectral vector based on a location matrix and a noise subspace matrix estimate.

Abstract: This invention relates to an adaptive detection system and method for analyzing range-doppler-azimuth data for target detection. The detection system has a threshold calculator for calculating a threshold value that is based on the standard deviation of the range-doppler-azimuth data and a predetermined probability of detection. The detection system also has a detection module in communication with the threshold calculator to receive the threshold value. The detection module calculates an estimated target amplitude and an estimated noise floor amplitude based on the range-doppler data that is located in a detection window. The detection module detects a target when the difference between the estimated target amplitude and the estimated noise floor amplitude is larger than the threshold value.

Abstract: This invention relates to a system and method for suppressing external interference in radar data provided by a plurality of sensors from a main sensor array, the data being pre-processed. The noise suppression system includes a first processing module and a second processing module. The first processing module receives the radar data and produces matched radar data while the second processing module receives the radar data and produces mis-matched radar data. The system further includes a beamformer that is in communication with the first processing module and an adaptive beamformer that is in communication with the second processing module and the beamformer. The beamformer receives the matched radar data and produces beamformed matched radar data.

Abstract: This invention relates to an adaptive detection system and method for analyzing range-doppler-azimuth data for target detection. The detection system has a threshold calculator for calculating a threshold value that is based on the standard deviation of the range-doppler-azimuth data and a predetermined probability of detection. The detection system also has a detection module in communication with the threshold calculator to receive the threshold value. The detection module calculates an estimated target amplitude and an estimated noise floor amplitude based on the range-doppler data that is located in a detection window. The detection module detects a target when the difference between the estimated target amplitude and the estimated noise floor amplitude is larger than the threshold value.