Beamspace direction finding based on the conjugate gradient algorithm

Abstract

Motivated by the performance of the direction finding algorithm based on the conjugate gradient (CG) method and the advantages of operating in beamspace, we develop a new beamspace direction finding algorithm, which we refer to as the beamspace conjugate gradient (BS CG) method. The recently developed Krylov subspace-based CG direction finding algorithm utilizes a non-eigenvector basis and yields a superior resolution performance for closely-spaced sources under severe conditions. However, its computational complexity is similar to the eigenvector-based methods. In order to save computational resources, we perform a beamspace transformation, which additionally leads to significant improvements in terms of the resolution capability and the estimation accuracy. A comprehensive complexity analysis and simulation results demonstrate the excellent performance of the proposed method and show its lower computational complexity.