Shi Yin, Xiaofang Wang, Lianyong Luo, Nan Pan, Da Zhao, Xiayang Zhang
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Collaborative strategy research of target tracking based on natural intelligence by UAV swarm
Regarding the regional area target collaborative tracking problem widely existing in intelligent scenarios, this paper built a distributed UAV swarm framework inspired by natural intelligence to heighten intricate missions’ efficiency. Also, a standoff collaboratively continuous tracking strategy was proposed based on a lateral guidance law with an improved Reference Point Guidance (RPG) and a longitudinal guidance law with an improved phase collaboration. Under an uncertain environment, this framework used an improved bat algorithm (IBA) to optimize the speed allocation of the UAV swarm’s online control strategy with information consensus estimation. Compared with a case without the designed transformation, statistically, the results demonstrate that the framework operates efficiently and robustly in phase error convergence, swarm flight distance, and fuel consumption, where a dynamic target exists.
期刊介绍:
The Journal of Aerospace Engineering is dedicated to the publication of high quality research in all branches of applied sciences and technology dealing with aircraft and spacecraft, and their support systems. "Our authorship is truly international and all efforts are made to ensure that each paper is presented in the best possible way and reaches a wide audience.
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