Hybrid Method of DOA Estimation Using Nested Array for Unequal Power Sources
Yunlong Yang, Xingpeng Mao · 2018
In the case of unequal power sources, due to the existence of strong sources, the performance of the subspace or compressive sensing (CS) based algorithms using a nested array suffers serious degradation for directions of arrival (DOAs) estimation of weak sources. In this paper, a hybrid estimation method is proposed to overcome this problem, and meanwhile is used to deal with underdetermined DOA estimation cases which are achieved by the nested array. In this hybrid method, CS-based algorithm is introduced first to estimate the DOAs of strong sources, which depends on the virtual uniform linear array (ULA) obtained from a nested array. Second, a covariance matrix with increased degrees of freedom, which is restored from the virtual ULA by Toeplitz matrix, is used to remove the effect of strong sources by orthogonal complement. Finally, the covariance matrix without strong sources can be used for estimating the DOAs of weak sources by MUSIC algorithm. Simulation results demonstrate the superior performance of the proposed method in terms of DOA estimation for unequal power sources.