Adaptive acoustic source localization algorithm based on wireless sensor networks

ZHANG Xiu; SHEN Xiao-hong; YAN Yong-sheng; WANG Hai-yan

doi:10.13873/J.1000-9787(2015)04-0115-04

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Adaptive acoustic source localization algorithm based on wireless sensor networks

更新时间：2025-09-11

- Adaptive acoustic source localization algorithm based on wireless sensor networks
- Vol. 34, Issue 4, Pages: 115-118(2015)
- 作者机构：
  
  西北工业大学航海学院
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2015)04-0115-04
  CLC： TN929.5;TP212.9
- Published：2015
- 稿件说明：
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[1]张秀,申晓红,闫永胜,王海燕.基于无线传感器网络的自适应声源定位算法[J].传感器与微系统,2015,34(04):115-118.

ZHANG Xiu, SHEN Xiao-hong, YAN Yong-sheng, et al. Adaptive acoustic source localization algorithm based on wireless sensor networks[J]. 2015, 34(4): 115-118.
[1]张秀,申晓红,闫永胜,王海燕.基于无线传感器网络的自适应声源定位算法[J].传感器与微系统,2015,34(04):115-118. DOI： 10.13873/J.1000-9787(2015)04-0115-04.

ZHANG Xiu, SHEN Xiao-hong, YAN Yong-sheng, et al. Adaptive acoustic source localization algorithm based on wireless sensor networks[J]. 2015, 34(4): 115-118. DOI： 10.13873/J.1000-9787(2015)04-0115-04.

摘要

基于声源能量的无线传感器网络（WSNs）最大似然定位算法抗噪声干扰能力强

定位精度高

同时适用于多个目标定位

但是计算量大

不适用于实时定位。针对现有算法的缺点

提出了一种基于自适应迭代的最大似然定位算法。该算法将代价函数作为目标函数

在给定的梯度误差范围内自适应地搜索目标位置。为了提高算法的收敛速度和定位精度

提出了基于Sigmoid函数的变步长的搜索算法。仿真实验结果表明:与最大似然定位算法相比

自适应迭代算法运算量小

定位精度高

能满足对目标定位精度和速度要求较高的场合

具有一定的实际应用意义。

Abstract

The maximum likelihood（ ML） localization algorithm for wireless sensor networks（ WSNs） based on acoustic source energy has strong anti-noise ability

high precision

and it is suitable for multiple targets localization at the same time; but it needs large amount of calculation and is not suitable for real-time positioning.Aiming at shortcoming of the existing algorithm

propose a maximum likelihood localization algorithm based on adaptive iteration. The new algorithm treats the cost function as objective function and search target location adaptively in given range of gradient error. Propose variable step size searching algorithm

based on Sigmoid function

in order to improve convergence speed and positioning precision. Simulation experiment result show that compared with the maximum likelihood localization algorithm

the proposed algorithm has less amount of calculation

high positioning precision

so it can meet the requirement of higher positioning precision and speed

has certain practical significance.

关键词

Keywords

references

WSN基于声音能量量化数据的目标定位研究 [J]. 戎舟. 计算机应用研究 . 2012(11)

基于RSSI&DFP的无线传感器网络声源目标定位算法 [J]. 刘立阳,张金成,吴中林,倪鹏. 传感技术学报 . 2011(10)

无线传感器网络自适应声音目标定位算法 [J]. 魏雅川,梁彦,陈延军,周问天. 传感技术学报 . 2010(03)

一种变步长LMS自适应滤波算法及分析 [J]. 高鹰,谢胜利. 电子学报 . 2001(08)

基于水下传感器网络的目标定位研究 [D]. 张子涵. 江苏科技大学 2012

无线传感器网络[M]. 清华大学出版社 , 孙利民等编著, 2005

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