Parameter Estimation of MIMO Radar Based on the OMP Algorithm

Abstract

This paper introduces the concept of compressed sensing (CS) into parameter estimation, and proposes a Multiple-input Multiple-output (MIMO) radar parameter estimation algorithm based on the Orthogonal Matching Pursuit (OMP) algorithm. In this algorithm, MIMO radar received signals are represented by joint sparse representation by establishing a sparse base. Then we use the random gaussian observation matrix and the OMP algorithm to reconstruct the target space to finish the estimation of target parameters. Moreover, the algorithm in this paper considers the radar signal model when array error exists, mainly discusses the influence of array amplitude error and phase error on the parameter estimation of MIMO radar based on OMP algorithm. Then the root mean square error (RMSE) of OMP algorithm and Compressive Sampling Matching Pursuit (COSAMP) algorithm are compared when the array error exists. Simulation shows that when the array amplitude and phase error exists, the estimation accuracy of the target's reflection amplitude and target parameters are reduced, and the OMP algorithm has a lower mean square error than the COSAMP algorithm. In conclusion, the proposed algorithm has high precision in parameter estimation. Even when array error exists, the OMP algorithm still has better performance in parameter estimation of MIMO radar target's reflection amplitude, azimuth Angle and pitch Angle than the COSAMP algorithm.