@inproceedings{539695ca82124d4681d1822aaab8820c,
title = "An Improved Particle Filter Algorithm for Automated Aerial Refueling Based on Meanshift Clustering",
abstract = "Traditional particle filter algorithm requires a number of particle samples for the accuracy of tracking with high computational complexity, which does not satisfy the real-time requirements. In addition, the target is easily to lose under the occlusion condition when the particle tracing algorithm is applied. A target tracking algorithm of anti-blocking particle filter is proposed in this paper. On the basis of clustering, a target probability density estimation method is proposed to describe the target model, and the target can be tracked with less particles. Kalman filter is chosen to determine the target location when the target is blocked seriously. Experiments show that when the algorithm is employed the robustness and tracking accuracy are much better and the real-time requirement is met.",
keywords = "automated aerial refueling, clustering, Kalman Filter, particle filter, template update",
author = "Zhuoya Wang and Jianguo Yan and Yaohong Qu and Shuai He",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018 ; Conference date: 10-08-2018 Through 12-08-2018",
year = "2018",
month = aug,
doi = "10.1109/GNCC42960.2018.9019016",
language = "英语",
series = "2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2018 IEEE CSAA Guidance, Navigation and Control Conference, CGNCC 2018",
}