DOD-DOA-Polarization Estimation in Large MIMO Radar System Based on Random Matrix Theory

This paper investigates the problem of estimating multiple parameters for large multi-input multi-output (MIMO) radar system in the situation that the numbers of the transmitter and receiver sensors are large that the number of samples could not satisfy the request to confirm that the population covariance matrix would be replaced by the sample covariance matrix. To obtain high-resolution in spatially close angle estimation for multi-target, multiple electromagnetic vector sensors at the receiver are equipped. A novel random matrix theory (RMT)-based approach is proposed to joint estimate the direction-of-departure (DOD), direction-of-arrival (DOA) and two polarization parameters based on two 2D G-MUSIC algorithms. The estimation performance of this paper outperforms that of the conventional algorithms since it has the ability to estimate the parameters more exactly when the number of samples is not sufficient compared with the numbers of the transmitter and receiver sensors. In addition, the exploit of polarization diversity has improved the resolution especially when two or more targets are too close to be distinguished. The simulation results validate the better performance of the proposed method compared with that of the conventional MUSIC algorithm.