基于到达时间的无线传感器网络协作定位算法

卢倩倩; 李有明; 常生明; 李娜娜

doi:10.11959/j.issn.1000−0801.2019004

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基于到达时间的无线传感器网络协作定位算法

研究与开发 | 更新时间：2024-06-05

- 基于到达时间的无线传感器网络协作定位算法
- Cooperative localization algorithm based on time-ofarrival in wireless senor network
- 电信科学 2019年35卷第1期页码：62-66
- 作者机构：
- 作者简介：
  
  [ "卢倩倩（1991− ），女，宁波大学信息科学与工程学院硕士生，主要研究方向为无线传感器网络中的协作定位技术。" ]
  [ "李有明（1963− ），男，宁波大学信息科学与工程学院教授、博士生导师，主要研究方向为宽带通信、电力线通信、协作中继、认知无线电等。" ]
  [ "常生明（1982− ），男，宁波大学信息科学与工程学院博士生，主要研究方向为无线传感器网络定位。" ]
  [ "李娜娜（1992− ），女，宁波大学信息科学与工程学院硕士生，主要研究方向为水声通信中的信号处理方法。" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(No.61571250);浙江省自然科学基金资助项目;The Natural Science Foundation of Zhejiang Province of China(No.LY18F010010)
- DOI：10.11959/j.issn.1000−0801.2019004
  中图分类号： TP929.5
- 网络出版日期：2019-01，
  
  纸质出版日期：2019-01-20
- 稿件说明：
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卢倩倩, 李有明, 常生明, 等. 基于到达时间的无线传感器网络协作定位算法[J]. 电信科学, 2019,35(1):62-66.

Qianqian LU, Youming LI, Shengming CHANG, et al. Cooperative localization algorithm based on time-ofarrival in wireless senor network[J]. Telecommunications science, 2019, 35(1): 62-66.
卢倩倩, 李有明, 常生明, 等. 基于到达时间的无线传感器网络协作定位算法[J]. 电信科学, 2019,35(1):62-66. DOI： 10.11959/j.issn.1000−0801.2019004.

Qianqian LU, Youming LI, Shengming CHANG, et al. Cooperative localization algorithm based on time-ofarrival in wireless senor network[J]. Telecommunications science, 2019, 35(1): 62-66. DOI： 10.11959/j.issn.1000−0801.2019004.

摘要

提出了一种基于到达时间的无线传感器网络协作定位方法。首先，建立关于目标位置的优化问题，其次通过运用混合半正定和二阶锥松弛理论，将原非凸优化问题转换为一种凸的优化问题，由此快速得到原问题的一个次优解。计算机模拟结果显示，新算法估计均方根误差更接近克拉美−罗界。

Abstract

A novel cooperative location method based on time-of-arrival in wireless senor networks was proposed. Firstly

the optimization problem for the target location was established. Secondly

the mixed semi-positive definite and second-order cone relaxation techniques were used to convert the original non-convex problem into a convex optimization problem. In this way

a fast suboptimal solution to the original problem was obtained. Finally

computer simulations show that the proposed method has lower root mean square error (RMSE) which is closer to the Cramer-Rao lower bound (CRB).

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references

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