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Journal of Projectiles, Rockets, Missiles and Guidance >

2025 , Vol. 45 >Issue 5: 633 - 641

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2025.05.006

Academic article

Research on Intelligent Minefield Single Target Tracking in Packet Loss and Asynchronous Environment

  • YUAN Hewei , 1 ,
  • WU Jun’an , 1, * ,
  • GUO Rui 1 ,
  • ZHAO Xu 2 ,
  • KONG Fanlin 3
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  • 1 School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 710065,Jiangsu, China
  • 2 Beijing Key Laboratory of High Dynamic Navigation Technology, Beijing University of Information Science and Technology, Beijing 100101, China
  • 3 Southwest Institute of Technical Physics, Chengdu 610041,Sichuan, China

Received date: 2024-09-11

  Online published: 2025-11-28

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Abstract

Intelligent minefields use acoustic detection systems and wireless sensor networks to locate and track strike targets.However,due to the complex and varied application scenarios of minefields,as well as the susceptibility to interference,if the sound detection sensor is damaged or the detection effect is unstable due to environmental factors,the acoustic detection system is difficult to output stable measurement information,which can lead to detection packet loss and misidentification;Due to the different initial sampling times,sampling periods,and information transmission delays of each landmine node in the minefield,the measurement information of each node is asynchronous;Due to environmental interference,network congestion may occur during communication in minefield networks,resulting in communication packet loss.A distributed Kalman filtering algorithm based on average consistency is proposed to address the above issues.Each node analyzes the validity of measurement information,processes invalid measurements into a filter,obtains local posterior state estimates,and performs time alignment.The time aligned local posterior state estimates are fused based on the average consensus algorithm to obtain global posterior state estimates.The experimental results show that the proposed method can still locate and track targets in asynchronous networks with obvious detection loss and misidentification phenomena,with a positioning accuracy of up to 5m,meeting the positioning requirements of intelligent minefields and providing an effective and feasible solution for collaborative positioning of intelligent minefields in complex application environments.

Key words： asynchronous network; detecting packet loss; average consistency filter; distributed kalman filter

Cite this article

YUAN Hewei , WU Jun’an , GUO Rui , ZHAO Xu , KONG Fanlin . Research on Intelligent Minefield Single Target Tracking in Packet Loss and Asynchronous Environment[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2025 , 45(5) : 633 -641 . DOI: 10.15892/j.cnki.djzdxb.2025.05.006

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