Detection and Estimation of Multiple Point Targets for LFM Echo Using Compressed Sensing

Abstract

Detection of high bandwidth linear frequency modulated (LFM) echo signal at Nyquist rate with traditional Matched Filter (MF) requires very high sampling rate that necessitates a high rate ADC which is expensive. With large amount of sampled data, storage capacity and power consumption increase. Also low resolution and range sidelobes of MF cause false alarms and masking of weak targets. Compressed Sensing (CS) enables the reconstruction of a sparse signal from a small set of measurements. In this paper, target ranges are estimated directly from compressed measurements without echo reconstruction. Receiver operating characteristic (ROC) curves for probability of detection were plotted. A comparative study is made for CS with MF in noise-free and noisy conditions. Target detection and estimation is done with just 8% of original echo samples in noise-free case and with 20% samples in noisy case of SNR = 20 dB. Also closely spaced targets could be detected with high resolution than MF. No Side lobes appear with CS and hence no false alarms can occur.KeywordsCompressed sensingSparsityMatched filter