Data Association Based Fast Fault Detection for Low-Cost Micro/Nano-Satellite

Rongli Chen, Xiaodong Wang, Yangming Guo, Weihua Qin, Ximing Zhang

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Under most circumstances, it is very important to achieve fast and real-Time low-cost micro/nano-satellite fault detection. Regarding of faults as dynamic modes which observe through the multi-sensors, with probabilistic data association based on multi-sensor, we obtain the fault detection results according to the association probability and the threshold values. Joint Probabilistic Data Association (JPDA) algorithm is one of the effective ways for multi-sensor and multi-Target tracking. We improve the JPDA algorithm as follows: At first, we propose an approximation method for constructing the confirmation matrix by removing the small probability events using the right threshold, and then, we present the mathematical division of the confirmation matrix according to the intersection area of the association gate of fault targets to be tracked; Finally, we compute the association probability of fault targets through attenuating the value of the public measurement. The simulation results show preliminarily that our improved JPDA algorithm saves the computational time greatly, and meet the requirements of fast and real-Time fault detection effectively.

源语言英语
主期刊名Proceedings of 2020 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2020
编辑Yong Qin, Ming J. Zuo, Xiaojian Yi, Limin Jia, Dejan Gjorgjevikj
出版商Institute of Electrical and Electronics Engineers Inc.
1-4
页数4
ISBN(电子版)9781728170503
DOI
出版状态已出版 - 5 8月 2020
活动4th International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2020 - Virtual, Beijing, 中国
期限: 5 8月 20207 8月 2020

出版系列

姓名Proceedings of 2020 International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2020

会议

会议4th International Conference on Sensing, Diagnostics, Prognostics, and Control, SDPC 2020
国家/地区中国
Virtual, Beijing
时期5/08/207/08/20

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