A Mechanism for Recognizing and Suppressing the Emergent Behavior of UAV Swarm

作者：Liu, Qiang; He, Ming^*; Xu, Daqin; Ding, Ning; Wang, Yong

来源：Mathematical Problems in Engineering, 2018, 2018: 6734923.

DOI：10.1155/2018/6734923

• SELF-ORGANIZATION
• DIVERGENCE
• FLOCKING
• NETWORKS
• DYNAMICS
• SYSTEMS

Similar to social animals in nature, UAV swarm is also a complex system that can produce emergent behavior. The emergent behavior of UAV swarm in specific airspace is undoubtedly the act that the defense side does not expect to see; therefore, recognition and suppression of the emergent behavior of UAVs swarm are needed. Based on the analysis of the UAV swarm emergent behavior mechanism, by adopting f-divergence method, UAV swarm emergent behavior was quantified, and a rapid recognition mechanism of emergent behavior has been established, thus, making preparation for the suppression of the emergent behavior. In the academic circle, for the first time, in accordance with heuristic rules governing the algorithms of UAV swarm suppression, principle of emergent behavior suppression has been proposed, failure judgment model of UAV swarm control under interference conditions has been constructed, the stability of UAV swarm has been analyzed, and the combat command process of UAV swarm based on OODA loop has been put forward. Through the simulation, the comparison of information entropy and f-divergence based emergence measurement method has been made, and f-divergence based method has some advantages for measuring the emergence of UAV swarm. From the analysis and discussion of the inhibitory effect on swarm flocking behavior under different interference intensity and timing, conclusion has been drawn that comprehensive suppression on the premise of correct recognition of flocking behavior is the best strategy fighting against UAV swarm emergent behavior.

• 出版日期2018
• 单位南京信息工程大学; 中国人民解放军军事医学科学院; 中国人民解放军海军指挥学院; 中国人民解放军国防大学