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Localization Algorithm Based on a Spring Particle Model (LASPM) for Large-Scale Unmanned Aerial Vehicle Swarm (UAVs)

Author

Listed:
  • Sanfeng Chen

    (Shenzhen Institute of Information Technology, China)

  • Guangming Lin

    (Dongguan City University, China)

  • Tao Hu

    (Shenzhen Institute of Information Technology, China)

  • Hui Wang

    (Shenzhen Institute of Information Technology, China)

  • Zhouyi Lai

    (Shenzhen Institute of Information Technology, China)

Abstract

A new localization algorithm based on large scale unmanned aerial vehicle swarm (UAVs) is proposed in the paper. The localization algorithm is based on a spring particle model (LASPM). It simulates the dynamic process of physical spring particle system. The UAVs form a special mobile wireless sensor network. Each UAV works as a highly-dynamic mobile sensor node. Only a few mobile sensor nodes are equipped with GPS localization devices, which are anchor nodes, and the other nodes are blind nodes. The mobile sensor nodes are set as particles with masses and connected with neighbor nodes by virtual springs. The virtual springs will force the particles to move to the original positions. The blind nodes' position can be inferred with the LASPM algorithm. The computational and communication complexity doesn't increase with the network scale size. The proposed algorithm can not only reduce the computational complexity, but also maintain the localization accuracy. The simulation results show the algorithm is effective.

Suggested Citation

  • Sanfeng Chen & Guangming Lin & Tao Hu & Hui Wang & Zhouyi Lai, 2023. "Localization Algorithm Based on a Spring Particle Model (LASPM) for Large-Scale Unmanned Aerial Vehicle Swarm (UAVs)," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 17(1), pages 1-13, January.
    • Handle: RePEc:igg:jcini0:v:17:y:2023:i:1:p:1-13
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