Research on DV-HOP localization algorithm based on adaptive particle swarm optimization

Cui Zhao; Yu-ran Hao

doi:10.1117/12.2660258

3 February 2023 Research on DV-HOP localization algorithm based on adaptive particle swarm optimization

Cui Zhao, Yu-ran Hao

Proceedings Volume 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022); 1251128 (2023) https://doi.org/10.1117/12.2660258
Event: Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 2022, Hulun Buir, China

Abstract

Aiming at the problem of low localization accuracy in Distance Vector-Hop (DV-Hop) algorithm, a localization algorithm based on adaptive PSO algorithm was proposed for wireless sensor networks. First of all, through single jumped average error correction average distance, and then using the average jump from receiving much of the anchor node estimate the distance between the nodes, to optimize estimated distance, the adaptive particle swarm optimization algorithm was used to optimize the position of the unknown node coordinates obtained by least square method, avoid APSO algorithm using adaptive operator algorithm trapped in local optimum, and get the global optimal. Simulation results show that the proposed algorithm is better than DV-Hop algorithm and PSO-DVHop algorithm in positioning accuracy under different anchor ratio, node number and communication radius.

Citation Download Citation

Cui Zhao and Yu-ran Hao "Research on DV-HOP localization algorithm based on adaptive particle swarm optimization", Proc. SPIE 12511, Third International Conference on Computer Vision and Data Mining (ICCVDM 2022), 1251128 (3 February 2023); https://doi.org/10.1117/12.2660258

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KEYWORDS

Particle swarm optimization

Sensor networks

Wireless communications

Sensors

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