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一种高分辨率的时间逆转方法,用于在反射环境中定位目标
Huiying Ma1,2, Tao Shang1,2, Gufeng Li1,2
1State Key Laboratory of Integrated Service Network, Xidian University, Xi'an 710071, China.
Sensors (Basel, Switzerland)
|May 25, 2024
概括
本研究介绍了一种新的声音源本地化 (SSL) 方法,使用时间逆转和稀疏的贝叶斯式学习,用于响应环境中的宽带低频信号. 该方法实现了强大的高分辨率本地化,有效地克服了多路径效应.
科学领域:
- 声学 声学 在声学方面
- 信号处理 信号处理
- 机器学习 机器学习
背景情况:
- 反响显著降低了声音源定位 (SSL) 方法的性能.
- 宽带低频信号在现实世界的声学环境中普遍存在.
- 现有的SSL技术与反响引起的多路径效应作斗争.
研究的目的:
- 开发一种强大的高分辨率SSL方法,用于声条件下的宽带低频信号.
- 利用时间逆转 (TR) 和稀疏贝叶斯式学习 (SBL) 的优势,提高本地化准确性.
- 为应对多路径传播和环境噪声带来的挑战.
主要方法:
- 在反响环境中研究了声音传播模型.
- 使用时间逆转 (TR) 来实现适应性聚焦并减轻多路径效应.
- 利用稀疏贝叶斯式学习 (SBL) 进行准确的波方向估计和源定位.
- 通过在声室中进行广泛的模拟和实验,验证了拟议的方法.
主要成果:
- 拟议的TR-SBL方法在定位宽带低频声源方面证明了令人满意的空间分辨率.
- 性能通过各种参数进行评估,包括带宽,麦克风阵列大小,SNR和反响时间.
- 该方法在离网条件下以及在具有挑战性的反响环境中被证明是可靠的.
结论:
- 开发的SSL方法有效地克服了反响和多路径干扰.
- 集成TR和SBL为准确的声音源定位提供了一个强大的方法.
- 拟议的技术在音响复杂环境中的实际应用方面显示出显著的前景.
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