Suppressing Interference from Noise in Sound Source Localization with Distributed Multisensor Array

To suppress interference from discrete noise of underwater sound sources, we apply matched field processing with multiple-constraint noise suppression (MNS MFP) to a distributed multisensor array. Optimal weight vectors and coherent processing are also combined with MNS MFP. The results from simulat...

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Bibliographic Details
Published in:Sensors and materials 2020-01, Vol.32 (8), p.2813
Main Authors: Zheng, Shengjia, Zheng, Wenjie, Shu, Jian, Li, Tiejun, Chen, Chin-Cheng, Jin, Fanzhu
Format: Article
Language:English
Subjects:
Acoustic noise
Arrays
Interference
Localization
Mathematical analysis
Sound sources
Underwater acoustics
Vectors (mathematics)
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Summary:To suppress interference from discrete noise of underwater sound sources, we apply matched field processing with multiple-constraint noise suppression (MNS MFP) to a distributed multisensor array. Optimal weight vectors and coherent processing are also combined with MNS MFP. The results from simulations clearly show the effectiveness of the method to localize and differentiate noise and sound sources. The probability of successful sound source localization (SSL) for the new method is higher than 0.9 with an error range of 5% for depth and distance. In addition, it accurately locates a sound source and a noise source at the same distance from the multisensory array at a depth difference of 33 m. This localization ability is much improved from that of the conventional matched field processing (CMFP) and diagonal loading minimum variance distortionless response (DL-MVDR) methods. With further development, the proposed method is expected to provide more accurate and precise data for underwater acoustics studies.
ISSN:0914-4935
DOI:10.18494/SAM.2020.2790