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基于深海短水听器阵列压缩匹配场处理的双声源定位

Localization of Two Sound Sources Based on Compressed Matched Field Processing with a Short Hydrophone Array in the Deep Ocean.

作者信息

Cao Ran, Yang Kunde, Yang Qiulong, Chen Peng, Sun Quan, Xue Runze

机构信息

School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710072, China.

Key Laboratory of Ocean Acoustics and Sensing (Northwestern Polytechnical University), Ministry of Industry and Information Technology, Xi'an 710072, China.

出版信息

Sensors (Basel). 2019 Sep 3;19(17):3810. doi: 10.3390/s19173810.

DOI:10.3390/s19173810
PMID:31484441
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6749268/
Abstract

Passive multiple sound source localization is a challenging problem in underwater acoustics, especially for a short hydrophone array in the deep ocean. Several attempts have been made to solve this problem by applying compressive sensing (CS) techniques. In this study, one greedy algorithm in CS theory combined with a spatial filter was developed and applied to a two-source localization scenario in the deep ocean. This method facilitates localization by utilizing the greedy algorithm with a spatial filter at several iterative loops. The simulated and experimental data suggest that the proposed method provides a certain localization performance improvement over the use of the Bartlett processor and the greedy algorithm without a spatial filter. Additionally, the effects on the source localization caused by factors such as the array aperture, number of hydrophones or snapshots, and signal-to-noise ratio (SNR) are demonstrated.

摘要

被动多声源定位是水下声学中的一个具有挑战性的问题，特别是对于深海中的短水听器阵列而言。已经进行了几次尝试，通过应用压缩感知（CS）技术来解决这个问题。在本研究中，开发了一种CS理论中的贪婪算法并将其与空间滤波器相结合，并应用于深海中的双源定位场景。该方法通过在几个迭代循环中利用带有空间滤波器的贪婪算法来促进定位。模拟和实验数据表明，与使用巴特利特处理器和没有空间滤波器的贪婪算法相比，所提出的方法在定位性能上有一定的提高。此外，还展示了诸如阵列孔径、水听器数量或快照数量以及信噪比（SNR）等因素对源定位的影响。

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