Quantifying The Differences In Low Probability Of Intercept Radar Waveforms Using Quadrature Mirror Filtering

Low Probability of Intercept (LPI) radars are a class of radar systems that possess certain performance% characteristics causing them to be nearly undetectable by most modern digital intercept receivers, Consequently, LPI radar systems can operate undetected until the intercept receiver is much closer than the radar's target detector, The enemy is thus faced with a significant problem To detect these types of radar, new direct digital receivers that use sophisticated signal processing are required, This thesis describes a novel signal processing architecture, and shows simulation results for a number of LPI waveforms. The LPI signal detection receiver is based on Quadrature Minor Filter Bank (QMFB) Tree processing and orthogonal wavelet techniques to decompose the input waveform into components representing the signal energy in rectangular "tiles" in the time-frequency plane, By analyzing the outputs at different layers of the tree it is possible to do feature extraction, identify and classify the LPI waveform parameters, and distinguish among the various LPI signal modulations Waveforms used as input signals to the detection algorithm include Frequency Modulated Continuous Wave, Polyphase Codes, Costas Codes and Frequency Shift Keying/Phase Shift Keying waveforms. The output matrices resulting from the most relevant layers of the QMFB tree processing are examined and the LPI modulation parameters are extracted under various signal-to-noise ratios,