基于统计不相关矢量集的集中式定位算法  

Centralized Localization Algorithm Based on Statistical Uncorrelated Vector Set

作　　者：戴欢[1,2] 何磊[3] 顾晓峰[1,2] 

机构地区：[1]江南大学轻工过程先进控制教育部重点实验室,江苏无锡214122 [2]江南大学物联网工程学院,江苏无锡214122 [3]中国科学院苏州纳米技术与纳米仿生研究所,江苏苏州215123

出　　处：《计算机工程》2012年第24期74-77,共4页Computer Engineering

基　　金：中央高校基本科研业务费专项基金资助项目(JUSRP20914;JUDCF10031)

摘　　要：为降低接收信号强度指示所产生的测距误差对定位精度的影响,提出一种基于统计不相关矢量集的集中式定位算法。通过坐标变换简化双重中心化矩阵的求解过程,使用统计不相关矢量集构造双重中心化矩阵,从而计算出节点坐标。仿真结果表明,在测距误差比较大的情况下,该算法仍能有效降低测距噪声干扰、提高定位精度,适用于低成本硬件的无线传感器网络。In order to reduce the impact of received signal strength indicator ranging error on positioning accuracy,this paper proposes a new centralized localization algorithm based on statistical uncorrelated vector set.The solving equation of the double centered matrix can be simplified by coordinate transformation.In order to reduce the noise disturbance,a new double centered matrix is reconstructed using statistical uncorrelated vector sets,which can be used to calculate the node coordinates directly.Simulation results indicate that the proposed localization algorithm can improve the localization accuracy efficiently when the distance-measuring error is relatively large,which is particularly suitable for Wireless Sensor Network（WSN） nodes based on low cost hardware.

关 键 词：无线传感器网络 定位 接收信号强度指示 统计不相关矢量集 测距误差 

分 类 号：TN92[电子电信—通信与信息系统]