Two-Dimensional DOA Estimation Using One-Dimensional Search for Spherical Arrays

A Reduced-dimensional spherical harmonics MUSIC (RD-SHMUSIC) is proposed to solve the problem of high computational complexity of Multiple signal classification (MUSIC) algorithm for Twodimensional (2-D) Direction of arrival (DOA) estimation. The proposed algorithm first expresses the spherical harmonic steering vector as a linear weight of a uniform phase vectors. Via the Lagrange multiplier method, we can get a new search function to estimate elevations. At second step, the algorithm expresses the steering vector in another form, a linear weight of a vector which is constructed by associated Legendre functions. A search function to estimate azimuths can also be obtained. The proposed method only needs One dimensional (1-D) angle search, which means it has a large reduction of computational complexity compared to the traditional Spherical harmonics MUSIC (SHMUSIC). The simulation results show that the accuracy of the proposed method is better than Two-stage decoupled approach (TSDA) algorithm, and has close performance to that of SHMUSIC.