Applications of sensor arrays in acoustic and seismic signal processing.

摘要

This work investigates the applications of sensor arrays in the areas of acoustic and seismic signal processing. It comprises three papers.;The first paper explores the problem of blind source separation (BSS) for convolutive acoustic signals. It concentrates on the well known permutation and amplitude problems in frequency-domain BSS and proposes a new hybrid approach to solve them. This approach connects the separation processes across all frequency bins, and relies on a novel permutation control unit. This framework could greatly reduce computational load and improve separation performance. Synthesized and real-world experiments demonstrate its efficiency.;The second paper investigates a new array beamforming technique for noise reduction and speech enhancement in cars. The proposed beamformer, called a near-field regionally constrained generalized sidelobe canceller (NRC-GSC), can enhance the capability of both direction and distance discrimination in reverberant environments. Experiments in simulated automobile cabins show good noise and interference suppression for in-car sound sources.;The third paper examines the role that array processing techniques can play in the detection of underground tunnels. It investigates the attenuation analysis of Rayleigh waves (AARW) method, designs a data acquisition scheme, and proposes a new post-processing approach to reduce the influence of subsurface anomalies and instrument sensitivity. It employs array processing techniques and greatly improves the accuracy of traditional tunnel detection methods, allowing engineers to determine tunnel locations easily and reliably. Experimental results verify its effectiveness.