An Optimal Guidance Strategy for Moving-Target Interception by a Multirotor Unmanned Aerial Vehicle Swarm

• Published in: IEEE access Vol. 8; pp. 121650 - 121664
• Main Authors: Wang, Xi, Tan, Guanzheng, Dai, Yusi, Lu, Fanlei, Zhao, Jian
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Collision avoidance; Force; Formation flying; Guidance (motion); Interception; Matching; Missiles; Moving targets; Optimal matching; Position measurement; pursuit algorithms; Strategy; target interception; Task analysis; three-dimensional guidance law; Unmanned aerial vehicles
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2020.3006479

To solve the problem of intercepting a moving target by a multirotor unmanned aerial vehicle (UAV) swarm, an optimal guidance strategy is proposed. The proposed guidance law is based on the integration of the classic pure pursuit guidance law and Kuhn-Munkres (KM) optimal matching algorithm, and virtual force potential functions are used to avoid collision. The proposed optimal guidance strategy is demonstrated by simulation experiments. The simulation results indicate that with the proposed optimal guidance strategy, a UAV swarm can intercept a moving target while maintaining the predetermined formation, and during the formation flight, the collisions between UAVs or the target can be avoided. Through a comparative experiment, the proposed optimal matching algorithm is proven to significantly reduce the average per-sampling-period total flight distance of all the UAVs and accelerate the interception process, and the formation completion degree is improved.