A novel subspace partition method for fourth-order statistics based MUSIC algorithm
Wenxing Li, Yu Zhao · 2017
It is known that accurate partition of subspaces is important to fourth-order statistics based multiple signal classification (FO-MUSIC) algorithm. However, when the number of signals exceeds the number of array elements, the error of conventional subspace partition method will increase, and the performance of FO-MUSIC algorithm will decrease. A novel subspace partition method for FO-MUSIC algorithm is proposed in this paper. Subspaces can be divided properly by the proposed method according to the way of array expansion. Good performance of FO-MUSIC algorithm can be obtained. The validity of the proposed method is verified by simulation results.