计算机工程 ›› 2012, Vol. 38 ›› Issue (24): 74-77.doi: 10.3969/j.issn.1000-3428.2012.24.018

• 网络与通信 • 上一篇    下一篇

基于统计不相关矢量集的集中式定位算法

戴 欢 1a,1b,何 磊 2,顾晓峰 1a,1b   

  1. (1. 江南大学 a. 轻工过程先进控制教育部重点实验室;b. 物联网工程学院,江苏 无锡 214122; 2. 中国科学院苏州纳米技术与纳米仿生研究所,江苏 苏州 215123)
  • 收稿日期:2011-10-11 修回日期:2011-12-27 出版日期:2012-12-20 发布日期:2012-12-18
  • 作者简介:戴 欢(1983-),男,博士研究生,主研方向:无线传感器网络,模式识别,人工智能;何 磊、顾晓峰,教授、博士、博士生导师
  • 基金项目:
    中央高校基本科研业务费专项基金资助项目(JUSRP20914, JUDCF10031)

Centralized Localization Algorithm Based on Statistical Uncorrelated Vector Set

DAI Huan 1a,1b, HE Lei 2, GU Xiao-feng 1a,1b   

  1. (1a. Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education; 1b. School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China; 2. Suzhou Institute of Nano-tech and Nano-bionics, Chinese Academy of Sciences, Suzhou 215123, China)
  • Received:2011-10-11 Revised:2011-12-27 Online:2012-12-20 Published:2012-12-18

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。

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

Abstract: 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.

Key words: Wireless Sensor Network(WSN), localization, Received Signal Strength Indicator(RSSI), statistical uncorrelated vector set, ranging error

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