在海洋环境中使用多尺度相关联网络和网络频谱距离进行远程被动声信号检测
Hongwei Zhang1, Haiyan Wang2, Xuanming Liang3
1Key Laboratory of Ocean Acoustics and Sensing (Northwestern Polytechnical University), Ministry of Industry and Information Technology, 127 Youyi West Road, Beilin District, Xi'an, Shaanxi 710072, China.
The Journal of the Acoustical Society of America
|September 11, 2023
概括
本研究引入了一种用于检测弱海洋声信号的新型网络表征方法,提高检测概率并降低信号噪声比要求,以提高海上安全.
科学领域:
- 海洋声学 海洋声学
- 信号处理 信号处理
- 网络科学 网络科学
背景情况:
- 在海洋环境中检测声信号对于安全和运营至关重要.
- 现有的方法往往依赖于事先的信息,限制了它们的适应性.
- 在复杂的海洋条件下,弱信号检测仍然是一个挑战.
研究的目的:
- 开发一种新的方法,使用网络特征来检测声信号.
- 将声信号检测转化为网络特征问题.
- 为了提高在海洋环境中弱声信号的检测.
主要方法:
- 建议采用多尺度关联网络 (MCN) 构建方法.
- 在不同的时间尺度上测量对对相关性,以构建网络表示.
- 引入了一种集信息几何学和图形信号处理的网络频谱距离方法,用于网络表征.
主要成果:
- 拟议的方法在信号与噪声比 (SNR) 为-18dB时,可以实现超过90%的检测概率.
- 现有方法要求SNR为-15dB,以获得可比的检测概率.
- 来自南中国海的全面模拟和现实数据验证了这一方法.
结论:
- 这种新的网络特征化方法显著改善了弱声信号检测.
- 与现有技术相比,这种方法提供了更高的性能,特别是在低SNR条件下.
- 该方法在港口安全,沿海运营和离岸活动方面具有有前途的应用.
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