Efficient Angle Estimation in MIMO Radar With Limited Antenna Resources via Rearranging Bayesian Tensor Analysis

In this letter, we investigate the angle estimation problem of multiple-input multiple-output (MIMO) radar with limited antenna resources. Considering the advantage of tensor structure, the received signal is constructed as a third-order complex-valued parallel factor (PARAFAC) model. Then, a Bayesian inference scheme combining tensor rearrangement and real-valued pre-processing is proposed, which obtains directions of departure (DoDs) and directions of arrival (DoAs) by fitting an optimized tensor model. The proposed scheme provides satisfactory angle estimation performance for the limited number of array antennas and the unknown number of targets. Simulation results demonstrate the robustness and effectiveness of the proposed scheme.