Three Dimensional MIMO Radar Imaging Using Sparse Model Based on Waveform Selection and Calibration Method in the Presence of Angle Imperfections

The effect of waveform selection on compressive sensing MIMO radar imaging using sparse model and an improved calibration method in the presence of angle imperfections are researched in this paper. Firstly the relationship between ambiguity function and Compressive Sensing (CS) dictionary coherence coefficient is analyzed. Then, in the presence of small spatial angle, an improved method based on Sparse Learning via Iterative Minimization (SLIM) algorithm is proposed to calibrate angle errors. Simulation results illustrate that the imaging quality can be enhanced when selected waveforms have low sidelobes and prove that the modifed method can calibrate angle errors effectively.