Fast DOA estimation based on MUSIC symmetrical compressed spectrum

To improve the speed of the estimation of direction of arrival (DOA) and decrease its computational complexity, a new spectrum called multiple signal classification (MUSIC) symmetrical compressed spectrum (MSCS) is proposed based on the analysis of the standard MUSIC algorithm. By creating the conjugate noise subspace, which equals to adding mirror sources in the symmetrical location of true DOAs, the dimension of the noise subspace is descended and MSCS is constructed by the singular value decomposing (SVD) on the intersection of noise subspace and its conjugate subspace. Theoretical analysis and simulation results show that MSCS can be used with arbitrary arrays. Moreover, the new method is capable of reducing the computational complexity of DOA estimation to 50% with a comparable precision to the conventional MUSIC algorithm.