匹配的静态共振增强了在非高斯冲动背景噪声下水下被动声纳检测
Haitao Dong1,2, Shilei Ma3, Jian Suo3
1Xi'an Key Laboratory of Intelligent Spectrum Sensing and Information Fusion, Xidian University, Xi'an 710071, China.
Sensors (Basel, Switzerland)
|May 11, 2024
概括
这项研究引入了一种新的匹配静态共振 (MSR) 方法,用于在具有挑战性的水下声纳环境中检测弱信号. 拟议的MSR探测器显著提高了性能,并减少了非高斯冲动噪声中的错误报警.
科学领域:
- 声学和信号处理
- 水下探测系统 水下探测系统
背景情况:
- 远程被动声纳检测依赖于低频谱线,但性能在复杂的非高斯冲动噪声下降.
- 高错误报警率是重尾冲动噪声环境中弱信号检测的一个重大挑战.
研究的目的:
- 建立一种基于匹配静态共振 (MSR) 的新型弱信号检测模型.
- 提出和评估两个基于MSR的探测器 (MSR-PED和MSR-PSNR),以提高声纳探测性能.
主要方法:
- 开发MSR输出响应分析的理论框架.
- 实施和测试MSR-PED和MSR-PSNR探测器.
- 在高斯式和非高斯式冲动噪声条件下的性能评估.
主要成果:
- 与传统方法相比,基于MSR的探测器在非高斯冲动噪声中表现出优异的性能.
- MSR-PSNR检测器显著优于基于能源的检测,克服了由重尾噪声引起的高误报警率.
- 与经典的PED方法相比,实现了显著的性能改进 (例如,MSR-PED的~16dB,MSR-PSNR的~22dB在α=1.5).
结论:
- 新的MSR-PSNR方法有效地解决了重尾冲动噪声中高误报率的挑战.
- 这项研究为在非高斯冲动环境中推进水下被动声纳检测提供了坚实的基础.
- 这些发现为未来研究在具有挑战性的声纳检测场景中提供了关键指导.
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