Weighted Decentralized Information Filter for Collaborative Air-Ground Target Geolocation in Large Outdoor Environments

Lele Zhang, Feng Gao, Bofan Chen, Lele Xi, Fang Deng*, Jie Chen

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

1 引用 (Scopus)

摘要

The unmanned air-ground vehicle system has been successfully applied in civil and military domains. Collaborative vision-based target geolocation with this system can provide an enduring and accurate estimate of moving target state. Traditional decentralized information filter (DIF) treated each platform in the system identically. In fact, the observation capabilities of aerial and ground platform typically differ from each other due to different configurations and changing sensor noises. Without considering these differences, the resources of each platform cannot be fully utilized. To handle the issue, we develop a weighted DIF for geolocating of moving targets via air-ground collaboration. Specifically, it can produce a weighted factor autonomously for each platform based on the similarity of tracks from the air-ground system. Then, it is able to have more accurate global estimates than the traditional filter. Finally, simulation experiments and actual tests are conducted and the results are presented to validate the efficacy of the proposed method. Additional details can be seen in our video submission.

源语言英语
页(从-至)7292-7302
页数11
期刊IEEE Transactions on Systems, Man, and Cybernetics: Systems
53
11
DOI
出版状态已出版 - 1 11月 2023

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