Direction-of-arrival tracking using a co-prime microphone array: A particle filter perspective

Abstract

Direction-of-arrival (DOA) estimation using a linear co-prime microphone array has attracted tremendous attention in many acoustic applications. Spatial smoothing MUSIC (SS-MUSIC)-based methods and compressive sensing-based methods are two popular approaches for DOA estimation using co-prime linear arrays. However, these methods exhibit high computational complexity and suffer from performance degradation under low signal-to-noise ratio conditions. This paper proposes a particle filter (PF)-based DOA tracking algorithm using a linear co-prime array. The proposed PF employs the current spatial information obtained from the array measurement and temporal information obtained from a constant-velocity motion model to estimate the DOA values recursively, which is a more suitable approach for real-world applications. An improved likelihood function model derived from the SS-MUSIC pseudo-spectra is implemented in the PF-based algorithm. Theoretical analyses and simulation results and the results of real acoustic data processing experiments are presented to demonstrate the effectiveness of the proposed PF-based algorithm.