Compressive sensing using S-transform in pulse radar
Compressive sensing is a novel approach for data acquisition at a sub-Nyquist rate. In this paper, we propose an algorithm using S-transform basis functions to adaptively sample pulse radar signals based on compressive sensing. Based on prior information from previously received pulse intervals, the algorithm adaptively samples the current interval at different resolutions. Exploiting the S-transform’s ability to extract phase information and its time and frequency localization properties, the proposed algorithm achieves target range and Doppler frequency detection in a significantly reduced processing time compared to competitor approaches. The simulation results using the receiver operating characteristic (ROC) curves shows the proposed algorithm performance in different scenarios.
|Keywords||Adaptive sampling, Compressive sensing, Delay-Doppler estimation, Radar sparse recovery, S-transform, Sub-Nyquist sampling|
|Conference||40th International Conference on Telecommunications and Signal Processing, TSP 2017|
Assem, A.M. (Assem M.), & Dansereau, R. (2017). Compressive sensing using S-transform in pulse radar. In 2017 40th International Conference on Telecommunications and Signal Processing, TSP 2017 (pp. 488–492). doi:10.1109/TSP.2017.8076034