Efficient 3D imaging method of MIMO radar for moving target

When compressive sensing (CS) was used to achieve sparse imaging of moving targets,the Doppler frequency caused by motion will increase the processing dimension,change the center frequency of echo and worsen the mutual coherence property of measurement matrix.In order to improve the three-dimensional (3D) imaging performance of MIMO radar for moving targets,an efficient method was proposed.In each dimension,the distribution information of targets was searched respectively and a new low-dimensional measurement matrix was reconstructed accordingly,so the targets’ area was narrowed down.At the same time,in order to optimize the mutual coherence property of measurement matrix,Bayesian method was used to optimize the velocity-dimensional projection matrix to reduce the strong mutual coherence brought by sampling of Doppler frequency,then the efficient sparse imaging could be achieved.The simulation results show that proposed method can improve the efficiency,accurate imaging performance with efficient.