High-Resolution Source Localization Algorithm Based on the Conjugate Gradient

Abstract

This paper proposes a new algorithm for the direction of arrival (DOA) estimation of P radiating sources. Unlike the classical subspace-based methods, it does not resort to the eigendecomposition of the covariance matrix of the received data. Indeed, the proposed algorithm involves the building of the signal subspace from the residual vectors of the conjugate gradient (CG) method. This approach is based on the same recently developed procedure which uses a noneigenvector basis derived from the auxiliary vectors (AV). The AV basis calculation algorithm is replaced by the residual vectors of the CG algorithm. Then, successive orthogonal gradient vectors are derived to form a basis of the signal subspace. A comprehensive performance comparison of the proposed algorithm with the well-known MUSIC and ESPRIT algorithms and the auxiliary vectors (AV)-based algorithm was conducted. It shows clearly the high performance of the proposed CG-based method in terms of the resolution capability of closely spaced uncorrelated and correlated sources with a small number of snapshots and at low signal-to-noise ratio (SNR).