完全分布式无线传感网中基于稀疏重构的声源定位  

Sound Source Location Based on Sparse Reconstruction in Fully Distributed Wireless Sensor Networks

作　　者：冯玉武 胡国华[1] 查长军[1] FENG Yu-wu;HU Guo-hua;ZHA Chang-jun(College of Advanced Manufacturing Engineering,Hefei University,Hefei 230601,China)

机构地区：[1]合肥学院先进制造工程学院,合肥230601

出　　处：《白城师范学院学报》2020年第5期74-79,共6页Journal of Baicheng Normal University

基　　金：安徽省高校自然科学研究重点项目(KJ2017A531,KJ2019A0838);安徽省质量工程项目(2018hfjyxm05,2018hfmooc05,2018mooc349);合肥学院科研发展基金项目(19ZR04ZDB).

摘　　要：为了解决无线传感网中低功耗、多声源定位精度低的问题,文章提出了基于完全分布式结构的自适应性稀疏重构算法.完全分布式结构仅需局部的数据传输,每个传感器节点仅需将其检测到的能量值传输到其单跳范围内的邻居节点,同样也会接收来自单跳范围内的邻居节点检测到的数据,避免大量数据的远距离无线传输,达到减少能量消耗的目的.为了减少计算复杂度,提高定位精度,在稀疏重构算法中采用了自适应性冗余字典.最后利用鲁棒一致性算法对每个节点所得的估计值进行融合得到声源位置的全局估计值,进一步提高定位精度.In order to solve the problem of low power consumption and low accuracy of multi-source localization in wireless sensor networks,an adaptive sparse reconstruction algorithm based on fully distributed structure is proposed in this paper.This algorithm only needs local data transmission.Each sensor node only needs to transmit its detected value to its neighbor nodes,and also receives the detected data from the neighbor nodes in the single hop range,reducing the long-distance wireless transmission and energy consumption.In order to reduce the computational complexity and improve the localization accuracy,an adaptive redundant dictionary is used.Finally,the robust consistency algorithm is used to fuse the estimated values of each node to obtain the global estimation of the sound source location,which further improves the localization accuracy.

关 键 词：声源定位 完全分布式 无线传感网 稀疏重构 

分 类 号：S512.6[农业科学—作物学]