Mutual coupling self-calibration algorithm for uniform linear array based on ESPRIT

Abstract

By exploiting the banded symmetric and Toeplitz matrix model for the mutual coupling of uniformly linear array (ULA), an efficient self-calibration algorithm based on estimation of signal parameter via rotational invariance techniques (ESPRIT) is proposed. The DOA and mutual coupling parameters can be decoupled by a smart choosing of subarrays for ESPRIT method, and favorable DOA estimation can be provided without the knowledge of the sensor mutual coupling matrix. Based on the estimated DOAs, an accurate estimation of mutual coupling matrix (MCM) can also be achieved for the self-calibration of ULA. The DOA estimation and mutual coupling estimation could be completed without any angle-searching and iterative procedure, so its computational burden is low. The correction and efficiency of the proposed algorithm are verified by the computer simulation results.