High-dimensional MVDR beamforming based on a second unitary transformation

Abstract

Minimum variance distortion-less response (MVDR) beamforming is a popular method to spatial filtering among adaptive array signal processing. However, the inversion of sample covariance matrix, especially the high-dimensional complex-valued matrix’s inversion, is an inevitable obstacle to the real-time performance of the beamformer. In order to address this problem, a second unitary transformation (UT) technique is presented to transform the inversion of original high-dimensional (M-dimensional) complex-valued covariance matrix into two low-dimensional (M/2-dimensional) real-valued symmetrical sub-ones’ inversion. The proposed second unitary transformation minimum variance distortion-less response (SUT-MVDR) beamforming converts complex-valued computation to real-valued computation at the first UT stage, based on which the computational complexity of matrix’s inversion is reduced to about one fourth of the original at the second UT stage, depending on two half-size sub-matrices’ inversion. Numerical simulations show that the proposed beamformer has a higher computational efficiency and a better output signal-to-interference-plus-noise ratio (SINR) performance than other similar beamformers.