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Optimization Algorithm of RSSI Transmission Model for Distance Error Correction

  • Yong Liu
  • Ningning Li
  • Dawei Wang
  • Ti Guan
  • Wenting Wang
  • Jianpo LiEmail author
  • Na Li
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 157)

Abstract

In wireless sensor networks localization process, RSSI-based ranging methods mostly adopt the traditional logarithmic-distance path loss model. Its model parameters mostly adopt empirical values and ignoring the problem of changes in the surrounding environment during the node localization process. Thus, it is increasing the localization error and reducing the applicability of the algorithm. To solve this problem, this paper proposes an optimization algorithm of RSSI transmission model for distance error correction (RSSI-DEC) to optimize the path loss factor and the reference path loss between anchor nodes in the signal transmission model. FA algorithm and PSO algorithm are used to optimize the parameters of the model, and the model parameters adapted to the monitoring environment are obtained to correct the ranging error. The simulation results show that RSSI-DEC algorithm proposed in this paper can effectively improve node localization accuracy and environmental adaptability. The algorithm proposed in this paper has an average relative localization error of 9.17%.

Keywords

RSSI Localization error Parameters Correction 

Notes

Acknowledgements

This work was supported by “Research on Lightweight Active Immune Technology for Electric Power Supervisory Control System”, a science and technology project of State Grid Co., Ltd. in 2019.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Yong Liu
    • 1
  • Ningning Li
    • 2
  • Dawei Wang
    • 1
  • Ti Guan
    • 1
  • Wenting Wang
    • 3
  • Jianpo Li
    • 4
    Email author
  • Na Li
    • 4
  1. 1.State Grid Shandong Electric Power CompanyJinanChina
  2. 2.Shandong Cyber Security and Informationization Technology CenterJinanChina
  3. 3.State Grid Shandong Electric Power Company, Electric Power Research InstituteJinanChina
  4. 4.School of Computer ScienceNortheast Electric Power UniversityJilinChina

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