DOA Tracking for Multiple Sources Based on a Novel Measurement Association Mapping
Renzhou Gui, Jun Wei Zhao, Hao Liang, Mei Song Tong · 2021
Aiming at the problem of Direction-of-arrival (DOA) time-varying, a covariance matrix method with noise removal DOA tracking particle filter algorithm based on generalized label multi-Bernoulli (GLMB) filter is proposed in this paper. Since the measurement of the uniform linear array (ULA) is superimposed, this will cause the measurement association map (MAP) in the GLMB filter update step to mismatch. In order to make the measurement match successful, we propose a novel Measurement Association Mapping (NMAP) strategy. And then, using the MUSIC spatial spectrum function to replace the calculation of the likelihood function, which makes the weight better. The simulation results show that the scheme is feasible.