Governed by: Ministry of Industry and Information Technology of the People's Republic of China
Sponsored by: Northwestern Polytechnical University  Chinese Society Aeronautics and Astronautics
Address: Aviation Building,Youyi Campus, Northwestern Polytechnical University
Research on Trajectory Prediction of Drone Swarm
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Northwest Institute of Mechanical and Electrical Engineering

Clc Number:

V249.122

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    Abstract:

    The trajectory prediction model of traditional weapon control algorithm can not effectively predict the complex trajectory of drones.Besides, the existing research on complex trajectory prediction usually consider only one UAV, with the huge amount of calculation. To predict the trajectory of drone swarm quickly and accurately, a method of trajectory prediction for UAVs is proposed. After obtaining the track of drone swarm, it is firstly clustered based on DBSCAN method; Then the trajectory is determined to be simple or complex. Finally,Kalman Filter prediction was used for simple trajectory prediction, while LSTM(Long Short-Term Memory)network was used for complex trajectory prediction. The proposed model is more precise compared with the model using Kalman Filter, as well as consume less computing time compared with the model completely using LSTM network,which can meet the real-time requirement, as well as provide scientific basis for anti-UAV swarm calculation.

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zhanggenyuan, LIN ZHIWEI, TANG XU, LEI KAIWEN. Research on Trajectory Prediction of Drone Swarm[J]. Advances in Aeronautical Science and Engineering,2023,14(3):69-76

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History
  • Received:July 03,2022
  • Revised:September 27,2022
  • Adopted:October 08,2022
  • Online: April 25,2023
  • Published: