在城市环境中定位声源,深度信号消失)
Aaron C Meyer1, Adrian K Doran1, D Keith Wilson1
1Engineer Research and Development Center, U.S. Army Cold Regions Research and Engineering Laboratory, 72 Lyme Road, Hanover, New Hampshire 03755, USA.
The Journal of the Acoustical Society of America
|July 16, 2025
概括
这项研究引入了一种新的声源定位算法,使用复杂的Wishart分布来提高城市环境中的精度. 这种新方法的性能优于用于定位爆炸和移动车辆的传统技术.
科学领域:
- 声学 声学 在声学方面
- 信号处理 信号处理
- 城市环境监测 城市环境监测
背景情况:
- 城市声学信号面临的挑战包括散射,多路径反射和衍射.
- 传统的源代码本地化算法与这些复杂的环境影响作斗争.
- 复杂的Wishart分布有效地模拟分散信号的统计数据.
研究的目的:
- 为城市环境开发和验证一种新的声源本地化算法.
- 在复杂的声学条件下解决传统方法的局限性.
- 为了提高声源检测和位置的准确性.
主要方法:
- 开发了一个新的算法,将复杂的维沙特分布与分析信号模型相结合.
- 该算法使用在城市环境中收集的真实声学数据进行了测试.
- 对传统的基于振幅和基于相位的定位方法进行了性能评估.
主要成果:
- 对于爆炸和移动车辆的来源,都实现了准确的源位置估计.
- 与传统方法相比,新算法在所有测试的指标上都显示出更高的准确性.
- 验证数据是在瑞士瓦伦施塔特收集的,代表了一个现实的城市声学环境.
结论:
- 基于物理学的模型利用复杂的维沙特分布,成功地在具有挑战性的城市环境中定位声源.
- 这种方法比现有的声学定位技术有了显著的改进.
- 该研究验证了先进的统计信号处理在现实世界声学监测中的有效性.
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