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A new recognition and classification algorithm of underwater acoustic signals based on multi-domain features combination

机译:基于多域特征组合的水声信号识别与分类新算法

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摘要

A new algorithm is proposed in this paper to recognize and classify underwater acoustic signals including underwater acoustic communication signals, active sonar signals, ship-radiating noise and burst ocean ambient noise. The paper firstly analyzed the features of underwater acoustic signals in time domain, frequency domain and cyclostationarity domain. At the same time, the way of extracting features about these signals is researched. This algorithm combines the features above and chooses a decision tree classifier to realize the recognition and classification of different underwater acoustic signals. Finally, the effectiveness in different multipath channels is evaluated by simulation. The results have shown that this algorithm is capable of recognizing and classifying different underwater acoustic signals with better performance than algorithms using features in only one domain; and, its performance is robust in a multipath fading environment.
机译:本文提出了一种新的算法来识别和分类水下声信号,包括水下声通信信号,有源声纳信号,舰船辐射噪声和突发性海洋环境噪声。本文首先分析了水下声信号在时域,频域和循环平稳域的特征。同时,研究了提取这些信号特征的方法。该算法结合了以上特征,选择了决策树分类器,实现了对不同水下声信号的识别和分类。最后,通过仿真评估了在不同的多径信道中的有效性。结果表明,与仅在一个域中使用特征的算法相比,该算法能够对不同的水下声信号进行识别和分类,性能更高。而且,它在多径衰落环境中的性能很强。

著录项

  • 来源
  • 会议地点 Harbin(CN)
  • 作者单位

    National Key Laboratory of Science and Technology on Blind Signal Processing, Chengdu, Sichuan, 610041, China;

    National Key Laboratory of Science and Technology on Blind Signal Processing, Chengdu, Sichuan, 610041, China;

    National Key Laboratory of Science and Technology on Blind Signal Processing, Chengdu, Sichuan, 610041, China;

    National Key Laboratory of Science and Technology on Blind Signal Processing, Chengdu, Sichuan, 610041, China;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Analytical models; Read only memory;

    机译:分析模型;只读存储器;
  • 入库时间 2022-08-26 13:55:29

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