Compressive Sensing for Target DOA Estimation in Radar

Compressive Sensing (CS) is a newly developed technique which can accurately recover signals with only a few random samples, provided that the signals are sparse or compressible in a certain domain. In this paper, we aim to make use of the CS technique to improve the target direction of arrival (DOA) estimation performance in radar. The idea is deploying the limited number of array elements in a much longer aperture (where the inter-element spacing is non-uniform and much greater than half wavelength), and using CS technique to estimate the DOA of targets. Benefiting from the longer array aperture, higher DOA estimation accuracy can be achieved. Moreover, unlike the conventional DOA estimators, CS estimator won't produce strong grating lobes in the sparse array sampling scenario. Simulation results are presented to validate the effectiveness of the proposed CS-based DOA estimation.