Range-Doppler Imaging for Noise Radar via 2D Generalized Orthogonal Matching Pursuit

Abstract

Noise radar has superior electronic counter-countermeasure capabilities, but also suffers from high range-Doppler imaging sidelobes if traditional matched filtering receiver is used. In this letter, we explore the range-Doppler sparsity of the targets and formulate the range-Doppler imaging problem in noise radar as a generalized 2D sparse recovery (SR) model. The corresponding solver is proposed based on a modified orthogonal matching pursuit (OMP) algorithm. Different from traditional 2D SR based range-Doppler imaging method which assumes a repetitive transmit waveform, the proposed method can deal with the random waveforms varying among different pulses in noise radar. Simulation results show that the proposed method can yield a range-Doppler image with lower sidelobes, and is more robust to noise than other state-of-art algorithms.