Extended reduced-rank joint estimation of direction of arrival with mutual coupling for coherent signals

Abstract

This paper proposes an extended method for direction-of-arrival (DOA) estimation with unknown mutual coupling for coherent signals. The proposed method employs the forward/backward spatial smoothing to decorrelate the coherent signals in the process of rank reduction with the joint iterative subspace optimization approach. Then, the autocalibration of mutual coupling is performed based on the Capon's minimum variance criterion. Performance of the proposed method is compared with the state of the art algorithms in terms of DOA root-mean-square error and in terms of probability of successful estimation, where successful estimation is the case when the average of absolute DOA estimation error is within 2.5°. It is shown that the proposed method has a similar performance as the state of the art autocalibration methods while offering a lower computational complexity.