SBL-Based 2-D DOA Estimation for L-Shaped Array With Unknown Mutual Coupling

Abstract

Based on L-shaped array(LSA), a variety of algorithms for direction of arrival (DOA) estimation have been developed in recent years. However, conventional methods are sensitive to the mutual coupling which may cause the performance of the DOA estimation to degrade dramatically or even fail. In order to solve this problem, a new algorithm for DOA estimation is proposed in this paper. Different from the existing algorithms, the DOA estimation of LSA with mutual coupling is achieved from the perspective of sparse Bayesian learning. A hierarchical form of the Student t prior is used to enhance the sparsity of source signal and achieve excellent performance for angle estimation. In the meanwhile, the mutual coupling effect is compensated blindly by sacrificing some sensors as auxiliary components and the hyperparameters and parameters updates are obtained by the expectation-maximization method. Simulation results verify that the performance of our method is superior than that of the state-of-art methods, particularly in the scenario of highly correlated and coherent signals.INDEX TERMS DOA estimation, L-shaped array (LSA), mutual coupling, sparse Bayesian learning (SBL), Student t prior.

A 2-D Doa Estimation Algorithm for L-Shaped Array With Improved Computational Efficiency

“…Early research on these algorithms mostly stayed in one-dimensional (1D) array. Since 1D DOA estimation can only provide 1D estimation information of incident wave, there are many defects in practical application, so more and more researchers are engaged in the research of two-dimensional (2D) DOA estimation [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]. Among these research results, the 2D-MUSIC algorithm is one of the most classic algorithms in current 2D-DOA estimation research.…”

“…Different from the single structure of a 1D DOA estimation array, the structure of a 2D DOA estimation array is diverse and has an important impact on the estimation results. Among many array structures, L-shaped array has attracted more and more attention due to its simple structure, easy implementation, excellent estimation performance, and small Cramer-Rao bound (CRB) [14][15][16]. In the research on L-shaped arrays, a PM algorithm using one or two L-shaped arrays is proposed in [17].…”