Source Number Estimation Based on the Pressure and Particle Velocity Combined Processing for Acoustic Vector-Sensor Arrays

This paper aims to achieve accurate source number estimation (SNE) using the acoustic vector-sensor (AVS) arrays, which are crucial for array-based detection and sensing applications. To fully exploit the advantages of the AVS arrays, we integrates SNE into the pressure and particle velocity combined processing (P&PV-CP) framework. This innovative approach leverages the uncorrelated noise between pressure and particle velocity channels to enhance the effective signal-to-noise ratio (SNR). We introduce a novel method for constructing the cross-covariance matrix within this framework, addressing challenges where signals from specific directions may be attenuated due to spatial filtering induced by fixed observation angles. Theoretical analysis and simulations demonstrate that the proposed P&PV-CP framework, along with the new covariance matrix construction method, significantly enhances processing gain.