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Published on: March 13, 2017

在无线传感器网络中基于双层数据聚合技术的声源定位.

Yuwu Feng¹, Guohua Hu¹, Lei Hong¹

¹College of Advanced Manufacturing Engineering, Hefei University, Hefei 230000, China.

Sensors (Basel, Switzerland)

|April 12, 2025

概括

此摘要是机器生成的。

本研究介绍了用于无线传感器网络的双层数据聚合技术,以节省能源. 这种方法显著降低了能源消耗,延长了用于声源定位的网络寿命.

关键词:

声源的定位声源的定位数据聚合,数据聚合.数据冗余性数据冗余性能源消耗能源消耗能源消耗混合噪声模型的混合噪声模型无线传感器网络是一个无线传感器网络.

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相关实验视频

Last Updated: May 14, 2025

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Published on: February 8, 2019

科学领域:

无线传感器网络无线传感器网络
信号处理信号处理
声学定位局部化声学定位

背景情况:

由于传感器节点固有的功率限制,无线传感器网络 (WSN) 的能源效率是一个关键的挑战.
现有的方法经常因高能耗而扎,限制了网络寿命和运行范围.
在现实环境中精确的声源定位受到异常噪声特征的阻碍.

研究的目的:

提出一种创新的声源本地化框架,利用一种新的两级数据聚合技术.
尽量减少能源消耗,延长无线传感器网络的运行寿命.
为应对声学传感环境中异常噪声的挑战.

主要方法:

混合噪声模型的开发,以在现实世界的传感器数据中描述异常噪声.
实施两级数据聚合策略:用于类似测量的传感器级聚合和集群头级聚合以消除节点间冗余.
应用非线性代加权最小方程算法用于使用聚合传感器数据估计声源位置.

主要成果:

拟议的双层数据聚合大大减少了数据冗余,从而节省了大量的能源.
在模拟实验中,能源消耗至少减少了51%和43%.
声源定位的根平均平方误差 (RMSE) 保持在0.96.6以下.

结论:

新的双层数据聚合技术有效地提高了无线传感器网络的能源效率.
拟议的框架为在声源定位应用中延长网络寿命提供了可行的解决方案.
该方法展示了管理数据冗余和在噪音条件下提高本地化准确性的实用方法.