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

IEEE Transactions on Systems, Man, and Cybernetics(2023)

Beijing Inst Technol | Natl Univ Singapore | School of Electronic Engineering | Tongji Univ

Cited 1|Views16
Abstract
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.
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Key words
Collaborative air-ground system,decentralized estimation,vision-based target geolocation
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要点】:本文提出了一种加权的去中心化信息滤波器,通过考虑空中与地面平台观测能力的差异,提高了大型室外环境中协作定位移动目标的准确度。

方法】:通过为每个平台自主生成基于空地系统追踪相似度的加权因子,改进了传统的去中心化信息滤波器。

实验】:通过模拟实验和实际测试,验证了提出方法的有效性,具体数据集名称未在摘要中提及。