Efficient Direction-of-arrival Estimation Based on Semi-real-valued Capon

Subspace based Direction-Of-Arrival (DOA) estimators require usually the number of sources to be known in advance. If the number of sources is incorrectly estimated, the performance of those methods is able to deteriorate significantly. This paper presents a novel efficient Semi-Real-Valued Capon (SRV-Capon) algorithm for DOA estimation with unknown number of signals. Compared with state-of-the-art real-valued techniques suitable for only Centro-Symmetrical Arrays (CSAs), the proposed method can be used with arbitrary arrays. Unlike conventional Capon with heavy complex computations, SRV-Capon exploits only the real part of the array output covariance matrix, leading to a real-valued spectral search over only half of the total angular field-of-view, which hence reduces about 75% computational complexity. Theoretical analysis and simulations demonstrate the effectiveness of the proposed approach.