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Journal of Software Engineering
  Year: 2015 | Volume: 9 | Issue: 3 | Page No.: 631-640
DOI: 10.3923/jse.2015.631.640
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Improvement of DV-Hop Localization Based on Evolutionary Programming Resample

Wanli Zhang, Xiaoying Yang and Qixiang Song

In this study, the evolutionary programming algorithm with high stability, fast convergence and excellent performance on solving global optimization problem is introduced into DV-Hop localization algorithm and an improved DV-Hop localization algorithm based on evolutionary programming resample (EPRDV-Hop) is proposed to solve the error problem, which is brought by DV-Hop localization algorithm using trilateration or maximum likelihood estimation method to calculate the coordinates of the unknown node. After obtaining the estimated distances between the unknown nodes and anchor nodes, the initial position estimation is achieved based on the sampling. Then, the evolutionary programming based position resample is carried out. Finally, the final estimated position of the unknown node is obtained through an iterative manner. Simulation results show that EPRDV-Hop algorithm effectively improves the positioning accuracy of the node without additional hardware.
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How to cite this article:

Wanli Zhang, Xiaoying Yang and Qixiang Song, 2015. Improvement of DV-Hop Localization Based on Evolutionary Programming Resample. Journal of Software Engineering, 9: 631-640.

DOI: 10.3923/jse.2015.631.640






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