J4 ›› 2011, Vol. 38 ›› Issue (4): 154-159.doi: 10.3969/j.issn.1001-2400.2011.04.028

• 研究论文 • 上一篇    下一篇

无线传感器网络中的进化规划重采样定位算法

程伟;史浩山;李冬   

  1. (西北工业大学 电子信息学院,陕西 西安  710129)
  • 收稿日期:2010-05-12 出版日期:2011-08-20 发布日期:2011-09-28
  • 通讯作者: 程伟
  • 作者简介:程伟(1980-),男,西北工业大学博士研究生,E-mail: pupil119@126.com.
  • 基金资助:

    教育部博士点基金资助项目(20050699037)

Novel localization algorithm based on evolutionary programming resampling in WSN

CHENG Wei;SHI Haoshan;LI Dong   

  1. (School of Elec.& Info., Northwestern Polytechnical Univ., Xi'an  710129, China)
  • Received:2010-05-12 Online:2011-08-20 Published:2011-09-28
  • Contact: CHENG Wei

摘要:

为了对无线传感器网络中随机分布的节点进行更精确的定位,提出了一种基于进化规划重采样的定位算法.在初始阶段进行位置采样并求得初始位置估计后,利用小规模的进化规划进行位置的重采样优化, 然后使用迭代求得位置估计.在进化过程中,可以使用标准进化规划和元进化规划两种方法来得到重采样位置.仿真结果表明:对比同类算法,该算法将平均定位误差降低了20%左右; 相对于标准进化规划,采用元进化规划的重采样具有更强的自适应能力,对定位算法的精度提升更加显著.

关键词: 无线传感器网络, 节点定位, 进化算法, 标准进化规划, 元进化规划, 重采样

Abstract:

In order to obtain the geographic positions of random nodes in wireless sensor networks (WSN) more accurately, a new localization algorithm is proposed based on evolutionary programming resampling. After the initial position estimation is achieved based on the sampling, a small-scale evolutionary programming based position resampling is carried out, and then iterative refinement is done. In the evolution stage, two schemes, i.e., standard evolutionary programming and meta-evolutionary programming, can be employed respectively to acquire the resample positions. Simulation results show that, compared with the similar method, the proposed algorithm can reduce the mean error of location by about 20%; moreover, compared with the standard evolutionary programming method, the resamping by Meta evolutionary programming improves the localization accuracy more effectively, because of its better adaptability.

Key words: wireless sensor networks, node localization, evolutionary algorithms, standard evolutionary programming, meta-evolutionary programming, resampling

中图分类号: 

  • TP393