DOA Tracking for Coherently Distributed Sources with Particle Filter

In this work, an efficient direction of arrival (DOA) tracking method for coherently distributed sources is proposed. The central DOA and angle spread are estimated by the proposed method with a particle filter at each snapshot. The spectrum calculated by the distributed source parameter estimator (DSPE) is used as a pseudo-likelihood function for particle updating, which enables the particle filter to process sensor signals directly without estimating the source amplitude. The proposed method is compared with the total least square estimating signal parameter via rotational invariance technique and the fast implementation of a power iteration subspace updating (FAPI-TLS-ESPRIT). The proposed method is verified by Monte Carlo simulations, and simulation results show that the proposed method can achieve an excellent DOA tracking performance and outperforms the FAPI-TLS-ESPRIT method. In addition, the proposed method can simultaneously estimate the central DOA and angle spread.