AOA, Delay, and Complex Propagation Factor Estimation for the Monostatic MIMO Radar System

Abstract

In this paper, we propose a solution to find the angle of arrival (AOA), delay, and the complex propagation factor for the monostatic multiple-input multiple-output (MIMO) radar system. In contrast to conventional iterative computationally demanding estimation schemes, we propose a closed form solution for most of the previous parameters. The solution is based on forming an approximate correlation matrix of the received signals at the MIMO radar receiver end. Then, an eigenvalue decomposition (EVD) is performed on the formed approximate correlation matrix. The AOAs of the received signals are deduced from the corresponding eigenvectors. Then, the delays are estimated from the received signal matrix properties. This is followed by forming structured matrices which will be used to find the complex propagation factors. These estimates can be used as initializations for other MIMO radar methods, such as the maximum likelihood algorithm. Simulation results show significantly low root mean square error (RMSE) for AOAs and complex propagation factors. On the other hand, our proposed method achieves zero RMSE in estimating the delays for relatively low signal-to-noise ratios (SNRs).

Sea Clutter Suppression and Target Detection Algorithm of Marine Radar Image Sequence Based on Spatio-Temporal Domain Joint Filtering

“…Subspace decomposition method mainly includes using eigenvalue decomposition [ 31 , 32 , 33 , 34 ] and singular value decomposition (SVD) [ 35 , 36 , 37 , 38 ] to suppress sea clutter. Among them, the SVD method is a typical research content and a method based on the characteristics of the first-order Bragg peak of sea clutter in the Doppler domain.…”