Motion Behaviour Based Communication Range Estimation of Adversarial Drone Swarms

Abstract

Communication range is a crucial parameter that impacts the dynamic responses of traditional drone swarms, and accurate estimation of the communication range of adversarial drone swarms is essential to understanding the inner interaction of swarm members and designing more precise anti-swarm countermeasures. Especially when the drones in an adversarial swarm use short-range communications to exchange data, their internal communication behaviours are difficult to reconnoiter, and precisely estimating the swarm's communication range purely based on the sensed motion behaviours is a tough challenge. In this work, the principles and algorithms for communication range estimation of the artificial potential field based adversarial drone swarm are investigated. First, the attack and invasion based interaction approaches are proposed to trigger the swarm's dynamic responses, and it is found that the invasion based interaction approach is more effective when the adversarial swarm is under optimal steady-state; second, to adequately find the true communication range value while minimizing the impact on the adversarial swarm, an optimization framework is established to compute the intruder's optimal trajectory; finally, numerical simulations and comparative analyses are conducted, which demonstrate the effectiveness and advantages of the proposed motion behaviour based communication range estimation approaches.