A UAV track planning method based on improved and simplified particle swarm

Yubo Jiang; Huan He; Guangxue Wang; Yi Leng; Haonan Li

doi:10.1117/12.3054247

20 January 2025 A UAV track planning method based on improved and simplified particle swarm

Yubo Jiang, Huan He, Guangxue Wang, Yi Leng, Haonan Li

Author Affiliations +

Proceedings Volume 13515, Fourth International Conference on Advanced Manufacturing Technology and Electronic Information (AMTEI 2024); 1351520 (2025) https://doi.org/10.1117/12.3054247
Event: 4th International Conference on Advanced Manufacturing Technology and Electronic Information (AMTEI 2024), 2024, Chongqing, China

Abstract

The implementation of track deception jamming by multiple UAVs on enemy network radar has high requirements for cooperation between the UAVs. The complex and changeable air combat environment will cause UAVs to deviate from the preset track, and then affect the homology test effect of false track points. In order to plan the UAV flight track with high interference rate, this paper first constructs the track deception jamming model, and then establishes an evaluation function model based on the analysis of the UAV energy consumption, probability of being detected by enemy radar and ineffective interference rate. Finally, the standard particle swarm optimization algorithm is improved based on Logistic chaos mapping, Levy flight and greedy strategy and then the improved simplified particle swarm optimization algorithm is obtained. The simulation results show that the improved simplified particle swarm optimization algorithm has faster search speed and higher search accuracy, and the UAV flight track planning based on the evaluation function in this paper can obtain greater effective interference rate.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yubo Jiang, Huan He, Guangxue Wang, Yi Leng, and Haonan Li "A UAV track planning method based on improved and simplified particle swarm", Proc. SPIE 13515, Fourth International Conference on Advanced Manufacturing Technology and Electronic Information (AMTEI 2024), 1351520 (20 January 2025); https://doi.org/10.1117/12.3054247

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KEYWORDS

Unmanned aerial vehicles

Particles

Radar

Radar sensor technology

Particle swarm optimization

Detection and tracking algorithms

Computer simulations

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