OMP-Based Target Detection for Pulse-Doppler Radar

Sammanfattning

Radar systems transmit radio-frequency electromagnetic waves and receive the reflectedsignals from objects within their field of view. A surveillance radar aims todetect and estimate the state of targets in the surveillance volume. Traditional detectionalgorithms struggle in environments containing closely spaced objects or heavyclutter, resulting in false alarms or missed detections. Greedy compressed sensingalgorithms, such as Orthogonal Matching Pursuit (OMP), address this through aniterative process that identifies and subtracts the strongest component in the residualsignal, enabling detection of weaker targets masked by stronger ones. In thisMaster’s thesis, OMP was implemented and evaluated on both real and simulatedpulse-Doppler radar data, focusing on scenarios involving closely spaced targets andclutter-rich environments. The performance of the OMP detector was compared toa conventional Cell-Averaging Constant False Alarm Rate (CA-CFAR) detector. Aproposed hybrid of the two detectors, denoted CA-OMP, was also evaluated. Theresults indicate that the OMP detector can resolve closely spaced targets and targetsin the presence of strong clutter more effectively than CA-CFAR, particularlyin simulated data. However, on real data it is unable to fully suppress detectedsignal components, resulting in false alarms and degraded detection performanceacross the surveillance space. The CA-OMP detector exhibited improved detectionperformance on real data compared to the CA-CFAR detector, while mitigatingmost of the incorrect detections generated by the OMP algorithm.