Particle Filter Algorithm for DOA Tracking Using Co-Prime Array

摘要

In this letter, the problem of direction of arrival (DOA) tracking using co-prime array is studied. A novel particle filter (PF)-based DOA tracking algorithm is proposed to recursively estimate the DOAs based on the measurement model and the state transition model. A modified likelihood function model based on the propagator method (PM) pseudo-spectrum is devised to update the involved particles under lower SNR or less samples condition. Compared to the existing techniques, such as the spatial smoothing multiple signal classification method (SS-MUSIC), compressive sensing (CS) and conventional likelihood PF (CL-PF) methods, the proposed algorithm can exhibit improved performance in term of estimating accuracy and computational cost. Simulation studies are carried out to show the superiority of the proposed PF algorithm.