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关于声源定位和检测方法及其应用的调查
Gabriel Jekateryńczuk1, Zbigniew Piotrowski1
1Faculty of Electronics, Military University of Technology, 00-908 Warsaw, Poland.
Sensors (Basel, Switzerland)
|January 11, 2024
概括
本调查对声源本地化和检测方法进行了分类,分析了传统和人工智能驱动的技术. 它强调了军事和民用领域的应用,指导了声学检测的未来研究.
科学领域:
- 声学 声学 在声学方面
- 信号处理 信号处理
- 人工智能的人工智能
背景情况:
- 在各种科学和工程领域,声音源定位和检测至关重要.
- 现有方法的差异很大,需要有结构的概述才能有效地应用.
研究的目的:
- 提供音源定位和检测方法的全面分类.
- 分析传统和现代 (基于AI) 的方法.
- 为了指导选择适合特定应用的合适方法.
主要方法:
- 现有声音源定位系统的文献审查和分类.
- 基于传播模型的方法分析.
- 评估用于声学检测的机器学习和深度学习技术.
主要成果:
- 基于既定标准的声音源本地化方法的详细分类.
- 基于模型的传播与基于人工智能的技术的比较分析.
- 确定物理现象,数学关系和人工智能在本地化中的作用.
结论:
- 声源本地化方法包括各种物理,数学和人工智能驱动的方法.
- 这些技术对于军事和民用应用都至关重要.
- 未来的趋势指向在声学检测和定位方面先进的AI集成.
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