Low complexity method for signal subspace fitting - Electronics Letters

Introduction: It is shown in [1] that the weighted subspace fitting (WSF) method, a minimising technique, always outperforms the deterministic maximum likelihood (DML) estimator for the problem of the direction-of-arrival (DOA) estimation. However, the WSF estimator is still subject to high computational cost, partially attributable to the estimation of the signal subspace. In this Letter, the relation between the multi-stage Wiener filter (MSWF) [2] and the signal subspace is found, therefore leading to a low complexity method for signal subspace fitting (SSF). The new method does not require an estimate of the covariance matrix or its eigen-decomposition, thereby implying very low computational complexity. Moreover, since the new signal subspace can be spanned only by D matched filters of the MSWF, its dimension may be much less than the number of signals. Simulations will show that, when the incident signals are coherent, the novel estimator yields approximately consistent results with the WSF method.