Differential denoising bearing estimation for spatially distributed sources in unknown correlated noise

This paper deals with the problem of bearing estimation for spatially distributed sources in unknown spatially correlated noise. Assumed that the noise covariance matrix is centro-Hermitian, a differential denoising scheme is developed. Combined it with the classic DSPE algorithm, a differential denoising estimator is formulated. Moreover, in order to improve its bearing-estimated performance in case of low signal-to-noise ratio (SNR), a modified differential denoising estimator is proposed. Simulation results show the effectiveness of the proposed methods under the low SNR case. The impacts of angular spread and number of sensors are also investigated.