通过使用矢量传感器在时间扩散的扭曲通道中通过字典学习盲目检测弱信号
Rami Rashid1, Ali Abdi1, Zoi-Heleni Michalopoulou2
1Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, New Jersey 07102, USA.
JASA express letters
|June 24, 2025
概括
本研究介绍了一种使用词典学习 (DL) 进行盲目被动信号检测的方法,用于水下稀疏时间传播扭曲 (TSD) 频道. 该方法有效地检测TSD通道中的未知信号,提高检测概率.
科学领域:
- 水下声学 水下声学
- 信号处理 信号处理
- 机器学习 机器学习
背景情况:
- 水下环境对信号检测具有挑战,原因是时间扩散扭曲 (TSD) 稀疏.
- 现有的方法在TSD通道中与未知的信号和通道特征作斗争.
- 被动检测对于秘密行动和最大限度地降低系统复杂性至关重要.
研究的目的:
- 开发用于水下TSD通道的盲目被动信号检测方法.
- 估计和分离未知的信号从未知的通道冲动响应.
- 评估拟议方法的性能与现有技术相比.
主要方法:
- 用于信号和通道估计的词典学习 (DL) 算法.
- 为稀疏的TSD通道量身定制的日志概率比率探测器的开发.
- 通过模拟和来自矢量传感器的实验数据进行性能评估.
主要成果:
- 提出的基于DL的盲动方法成功估计和分离信号.
- 日志概率比率探测器在稀疏的TSD通道条件下显示出有效性.
- 与其他方法相比,水下实验验证了该方法的优越检测概率.
结论:
- 基于字典学习的盲动方法有效检测水下TSD通道中的未知信号.
- 这种方法在具有挑战性的声学环境中提供了更好的检测性能.
- 该方法提供了一个强大的解决方案,用于在没有先前信号知识的情况下被动信号检测.
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