Improved DOA estimators using partial relaxation approach

In this paper, the partial relaxation approach is introduced and applied to DOA estimation using spectral search. Unlike existing methods like Capon or MUSIC which can be considered as single source approximations of multi-source estimation criteria, the proposed approach accounts for the existence of multiple sources. At each direction, the manifold structure of interfering signals impinging on the sensor array is relaxed, which results in closed form estimates for the interference parameters. The conventional multidimensional optimization problem reduces, thanks to this relaxation, to a simple spectral search. Following this principle, proposed estimators based on the Deterministic Maximum Likelihood, Weighted Subspace Fitting and Covariance Fitting method are derived. Simulation results show that the performance of the proposed estimators is superior to conventional methods especially in the case of low SNR and low number of snapshots, irrespectively of the special structure of the sensor array.