电信科学 ›› 2014, Vol. 30 ›› Issue (10): 99-102.doi: 10.3969/j.issn.1000-0801.2014.10.015

• 研究与开发 • 上一篇    下一篇

网络随机指数噪声环境下时钟同步与定位的联合研究

赵响1,2,林基明2   

  1. 1 西安电子科技大学通信工程学院 西安 710071
    2 桂林电子科技大学信息与通信学院 桂林 541004
  • 出版日期:2014-10-15 发布日期:2017-06-29
  • 基金资助:
    国家自然科学基金资助项目

Joint Research on Clock Synchronization and Localization in Wireless Sensor Network with Stochastic Exponentially Distributed Noise

Xiang Zhao1,2,Jiming Lin2   

  1. 1 School of Telecommunications Engineering, Xidian University, Xi'an 710071, China
    2 School of Information and Communication, Guilin University of Electronic Technology, Guilin 541004, China
  • Online:2014-10-15 Published:2017-06-29

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摘要：

在无线传感器网络中，基于消息到达时间的时钟同步与定位联合研究是一项重要的研究课题。网络的随机时延一般用指数分布描述。基于消息到达时间的测量值，推出了在指数随机噪声条件下同步与定位的联合最大似然估计（JMLE）算法以及联合最佳线性无偏估计（JBLUE）算法。仿真表明，与已有的联合算法相比，提出的JMLE算法与JBLUE算法估计精度较高。

关键词: 联合最大似然估计, 联合最佳线性无偏估计, 指数分布, 定位, 同步

Abstract:

Joint clock synchronization and localization based on the time of arrival（TOA）measurements is a very important research topic for many wireless sensor network applications. The exponentially distributed link delay is usually used to describe the practical network link condition. The joint maximum likelihood estimation（JMLE）on clock synchronization and localization problem was first proposed based on the TOA measurements. JMLE was optimal only for Gaussian delay, as for the exponentially distributed delay, the joint best linear unbiased estimation （JBLUE）was then proposed. The result is derived via simulation: JMLE and JBLUE are always superior to the latest joint algorithm, with the highest estimation accuracy.

Key words: joint maximum likelihood estimation, joint best linear unbiased estimation, exponentially distributed, localization, synchronization

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