UAV Swarm Situational Awareness Technology Based on Static and Dynamic Comprehensive Estimations

‍ ‍With the rapid development of military unmanned aerial vehicle（UAV）technology， its combat system is gradually changing from single to swarm. To counteract the invasion of UAV swarms， it is critical to explore situational awareness technologies tailored for the scenario involving UAV swarm incursions. Currently，UAV swarm situational awareness field primarily focuses on the conceptual study of technologies and models， however， it lacks specific situational awareness technologies and simulation platforms tailored for concrete application scenarios. This paper introduces the attack formations of UAV swarm and the cooperative attack model of UAVs based on distributed warfare tactical scenarios and Harris hawk’s herding hunting model. The time difference of arrival （TDOA） and the joint probabilistic data association filter （JPDAF） are used to obtain the trajectory of the UAV swarm. The battlefield situation for the UAV swarm can be categorized into static and dynamic， representing the understanding of the battlefield situation at a given moment and the inference of future trends on the battlefield， respectively. On this basis， a UAV swarm situational awareness technology based on static and dynamic comprehensive estimations are proposed， including static situational awareness evaluated by fuzzy rules and dynamic situational awareness inferred from swarm predictions. Additionally， a three-dimensional UAV swarm situational awareness simulation platform is developed， where the processes of kinematic modeling， positioning tracking， battlefield situational awareness， and error analysis of invading UAV swarms are realized to verify the effectiveness of the proposed situational awareness technology.