Computationally Efficient DOA Estimation in a Multipath Environment Using Covariance Differencing and Iterative Spatial Smoothing

Abstract

High-resolution signal processing using sensor arrays to estimate the directions of unknown correlated signals in multipath environments is associated with high computational complexity. This paper proposes a computationally efficient direction of arrival (DOA) estimation algorithm. The algorithm is based on two stages of detection: a first stage for discriminating uncorrelated signals and a second stage for resolving the directions of arrival of correlated signals using covariance differencing and iterative spatial smoothing. Simulation results show that the proposed algorithm operates at a much lower computational cost compared to standard methods.