Research on Underwater Acoustic Target Depth Classification Based on Modal Filtering Characteristics of Long Horizontal Line Array

Guojun Xu, Weihua Zhang, Min Zhu, Jizhou Guo, Yanqun Wu, Jiahua Zhu
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引用次数: 2

Abstract

Considering the problem of depth classification of underwater acoustic targets in shallow water, a classification method based on modal filtering characteristics of long horizontal line array(HLA) beamforming in a negative thermocline environment was proposed. Based on normal mode theory, the spatial filtering characteristics of long HLA are studied by beamforming, and it was found that this characteristic can filter a normal mode. In the negative thermocline environment, the acoustic fields excited by deep and shallow sources and received by deep receivers are controlled by different modes. Surface reflection bottom reflection (SRBR) mode and non-surface reflection bottom reflection (NSRBR) mode show different interference structures in range-spectrum. Based on the characteristics of modal filtering and sound field classification, a depth classification method for shallow water acoustic targets in a negative thermocline environment is established. Numerical results show that the proposed method is robust and can effectively distinguish the acoustic source targets above or below the thermocline (surface and underwater targets) without knowing the specific acoustic environment parameters in advance.
基于长水平线阵模态滤波特性的水声目标深度分类研究
针对浅水水声目标深度分类问题,提出了一种基于负温跃层环境下长水平线阵列波束形成模态滤波特性的分类方法。基于正模理论,通过波束形成研究了长HLA的空间滤波特性,发现该特性可以滤除正模。在负温跃层环境下,深源和浅源激发的声场以及深源接收的声场受到不同模式的控制。表面反射底反射(SRBR)模式和非表面反射底反射(NSRBR)模式在距离光谱上表现出不同的干涉结构。基于模态滤波和声场分类的特点,建立了一种负温跃层环境下浅水声目标深度分类方法。数值结果表明,该方法具有较强的鲁棒性,能够在不事先知道具体声环境参数的情况下,有效区分温跃层上下的声源目标(水面和水下目标)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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