Path planning localization method for mobile anchor nodes in WSNs

Node positioning is one of the key technologies in wireless sensor networks, and positioning error and positioning coverage are two key indicators to measure the performance of node positioning, which have always been the focus of the research community. The article focuses on six representative mobile anchor node path planning positioning algorithms, including Σ-Scan, LH, LMAT, M-curves, N-curves, and TGS. Through comparative analysis, the effectiveness of these algorithms in reducing positioning error and improving positioning coverage is deeply discussed. To comprehensively and objectively evaluate the performance of the algorithms, this paper introduces the least squares method as the positioning algorithm to ensure the accuracy of the evaluation results. The experimental results show that all six algorithms demonstrate sensitivity to changes in the number of nodes and communication radius in terms of positioning error and positioning coverage.

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Publication Details

Published
2024-10-18
DOI
https://doi.org/10.1117/12.3049639
Primary Topic
Indoor and Outdoor Localization Technologies
Type
article
Field-Weighted Citation Impact
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article

Path planning localization method for mobile anchor nodes in WSNs

Wenyan Liu
Indoor and Outdoor Localization Technologies
article

Path planning localization method for mobile anchor nodes in WSNs

Wenyan Liu
article en

Abstract

Node positioning is one of the key technologies in wireless sensor networks, and positioning error and positioning coverage are two key indicators to measure the performance of node positioning, which have always been the focus of the research community. The article focuses on six representative mobile anchor node path planning positioning algorithms, including Σ-Scan, LH, LMAT, M-curves, N-curves, and TGS. Through comparative analysis, the effectiveness of these algorithms in reducing positioning error and improving positioning coverage is deeply discussed. To comprehensively and objectively evaluate the performance of the algorithms, this paper introduces the least squares method as the positioning algorithm to ensure the accuracy of the evaluation results. The experimental results show that all six algorithms demonstrate sensitivity to changes in the number of nodes and communication radius in terms of positioning error and positioning coverage.

Openalex Percentile: Top 84%
Indoor and Outdoor Localization Technologies
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