A fast DOA estimation algorithm based on subspace projection
Jingjing Cai, Peng Li, Yinping Zhang, Guoqing Zhao · 2014
The Multiple Signal Classification (MUSIC) algorithm is a representative method for the Direction of Arrival (DOA) estimation. However, it has to compute Eigenvalue Decomposition (EVD) and cumulate certain snapshots for once DOA estimation, which is costly in the computation and limits its applications. This paper proposes a Subspace Projection based MUSIC (SP-MUSIC) algorithm. The algorithm avoids computing EVD in the subspace estimation. It reduces the computational complexity and need not cumulate snapshots. Moreover, a Simplified SP-MUSIC (SSP-MUSIC) is devised, which accelerates the DOA estimation further. The computation and memory usage for the both algorithms are analyzed theoretically. The computational complexities are reduced greatly, especially for the SSP-MUSIC. And the SSP-MUSIC also takes a smaller memory capacity. Through the simulations, it is illustrated that the performance of the SP-MUSIC and the SSP-MUSIC is quit close to the traditional MUSIC.