Title: Range-based localisation algorithms integrated with the probability of ranging error in wireless sensor networks

Authors: Jianying Zheng; Yan Huang; Yiming Wang; Yang Xiao; C.L. Philip Chen

Addresses: The School of Urban Trail Transportation, Soochow University, Suzhou 215021, China ' The School of Electronics and Information, Suzhou Vocational University, Suzhou 215021, China ' School of Urban Trail Transportation, Soochow University, Suzhou 215006, China ' Department of Computer Science, University of Alabama, Tuscaloosa, AL 35487-0290, USA ' Faculty of Science of Technology, University of Macau, Macau, China

Abstract: In wireless sensor networks (WSNs), location information is regarded as essential information to achieve intelligent monitoring and control. Recently, a large number of range-based localisation algorithms were proposed. Nearly, all of the algorithms are based on least square method, in which the sum of all ranging error is treated as the performance index. The disadvantage is ignoring the probability characteristics of ranging error. This paper aims to integrate the ranging characteristic to improve the localisation accuracy. First, introducing a probability factor represents the credibility of distance measurement. Then, the probability factor is integrated into the optimised performance index, and the location of unknown sensor node are estimated and calculated. In addition, the method of determining the probability factor of the ranging information is also provided. Finally, we have performed many simulations to validate the performance of the localisation algorithms proposed. Experimental results show that the localisation accuracy is improved.

Keywords: WSNs; wireless sensor networks; range-based localisation; optimisation; ranging error probability; wireless networks; localisation accuracy; location information; simulation.

DOI: 10.1504/IJSNET.2014.059993

International Journal of Sensor Networks, 2014 Vol.15 No.1, pp.23 - 31

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 23 Mar 2014 *

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