Sparse self-calibration by map method for MIMO radar imaging

Multiple-input multiple-output (MIMO) radar is expected to achieve good inversion performance by utilizing space diversity technology. However, traditional imaging methods often fail owing to the practical constraints that the available transmitters and receivers are very few and the number of snapshots is very limited. More seriously, the unavoidable position errors of the transmitters and the receivers would further deteriorate the imaging results. In this paper, by exploiting the sparse priority of the target, the sparse self-calibration by maximum a posterior probability method (SSC-MAP) is proposed to provide high resolution image and realize accurate position calibration at the same time. Numerical simulations verify the effectiveness of the proposed method.