Sound Localization Using an Acoustic Vector Sensor Array with a Coded Cover

The coded cover basically compresses the signals impinging on it from a large virtual array to a smaller physical array of sensors. To recover the uncompressed covariance matrix of the virtual array represented by the coded cover, we adopt compressed covariance sensing (CCS). Experimental results show that a 14 × 10 coded cover combined with an array of 12 probes that measure both pressure and particle velocity enables accurate localization of up to 100 sound sources in three dimensions, even under challenging conditions with a signal-to-noise ratio (SNR) as low as 10 dB. Furthermore, to address the impact of geometric mismatch—which distorts the compression matrix—we incorporate a grid-search-based calibration method to correct these perturbations. The proposed approach demonstrates both scalability and robustness, making it a promising solution for large-scale sound source localization.