摘要

A second forward/ backward (SFB) averaging technique is presented to transform the real symmetrical covariance matrix of the popular unitary root-MUSIC (U-root-MUSIC) into a real bisymmetrical one, based on which a SFB-U-root-MUSIC direction of arrival estimation algorithm with reduced computational complexity is developed. The proposed SFB-U-root-MUSIC algorithm reduces the computational complexity in the eigenvalue decomposition (EVD) stage by a factor about four because it performs real-valued EVDs on two sub-matrices of about half sizes. The proposed SFB averaging technique is further extended as a generalized dimension reduction method to other unitary DOA estimators for low-complexity EVD computation, and numerical simulations are conducted to demonstrate, such a dimension reduction technique sacrifices statistically nonsignificant root mean square performance that is acceptable.