Sparsity-driven high resolution FDLFM-MIMO radar imaging

Frequency division linear frequency modulation multiple-input-multiple-output (FDLFM-MIMO) radar may provide an efficient way to synthesize a high-resolution range profile (HRRP) and has attracted more attention. Unfortunately, the conventional methods based on Matched Filter (MF) show high sidelobes and can not get the expected range resolution. In this paper, a sparsity-driven imaging method is proposed to overcome the drawback of low range resolution. Particularly for the HRRP synthesis, the algorithm aims to improve the accuracy of atoms chosen through solving the l₁-norm optimization problem and jointly relying on the set of collected atoms, the algorithm yields the HRRP with a good performance. The high resolution imaging is performed after the azimuth compression through the Inverse Discrete Fourier Transform (IDFT). Simulation results are given to verify the effectiveness of the proposed method.