Tracking multiple space objects using multiple surveillance sensors is a critical approach in many Space Situation Awareness(SSA) applications. In this process, the uncertainties of targets,dynamics, and observations ...Tracking multiple space objects using multiple surveillance sensors is a critical approach in many Space Situation Awareness(SSA) applications. In this process, the uncertainties of targets,dynamics, and observations are usually represented by the probability distributions. However, precise characterization of uncertainty becomes challenging due to imperfect knowledge about some key aspects, such as birth targets and sensor detection profiles. To overcome this challenge, this paper proposes a multi-sensor possibility PHD filter based on the theory of outer probability measures. An effective compensation method is introduced to tackle variations in the fields of view of SSA sensors or instances of missed detections, aiming to mitigate the inconsistency in localized information. The proposed method is adapted to centralized and distributed sensor networks, offering effective solutions for multi-sensor multi-target tracking. The major innovation of the proposed method compared with typical methods is the proper description of epistemic uncertainty, which yields more robust performance in the scenarios of lacking some information about the system.The effectiveness of the multi-sensor possibility PHD filter is demonstrated by a comparison with conventional methods in two simulated scenarios.展开更多
Chuan Qin,MD,PhD,is the President of the Chinese Association for Laboratory Animal Sciences(CALAS),and the permanent professor of Chinese Academy of Medical Sciences(CAMS)&Peking Union Medical College(PUMC).Moreov...Chuan Qin,MD,PhD,is the President of the Chinese Association for Laboratory Animal Sciences(CALAS),and the permanent professor of Chinese Academy of Medical Sciences(CAMS)&Peking Union Medical College(PUMC).Moreover,she is the senior scientist of Institute of Laboratory Animal Sciences(ILAS),CAMS&PUMC.She is also the Vice-President of the Asian Federation of Laboratory Animal Science Associations(AFLAS),a board member of the International Council for Laboratory Animal Science(ICLAS),and Chairman of the National Standardization Technical Committee of Laboratory Animals.In addition to Animal Models and Experimental Medicine,Prof.Qin is also the Editor-in-Chief of Acta Laboratorium Animalis Scientia Sinica and Chinese Journal of Comparative Medicine.展开更多
基金funded by the National Natural Science Foundation of China(No.12202049)the Beijing Institute of Technology Research Fund Program for Young Scholars,China.
文摘Tracking multiple space objects using multiple surveillance sensors is a critical approach in many Space Situation Awareness(SSA) applications. In this process, the uncertainties of targets,dynamics, and observations are usually represented by the probability distributions. However, precise characterization of uncertainty becomes challenging due to imperfect knowledge about some key aspects, such as birth targets and sensor detection profiles. To overcome this challenge, this paper proposes a multi-sensor possibility PHD filter based on the theory of outer probability measures. An effective compensation method is introduced to tackle variations in the fields of view of SSA sensors or instances of missed detections, aiming to mitigate the inconsistency in localized information. The proposed method is adapted to centralized and distributed sensor networks, offering effective solutions for multi-sensor multi-target tracking. The major innovation of the proposed method compared with typical methods is the proper description of epistemic uncertainty, which yields more robust performance in the scenarios of lacking some information about the system.The effectiveness of the multi-sensor possibility PHD filter is demonstrated by a comparison with conventional methods in two simulated scenarios.
文摘Chuan Qin,MD,PhD,is the President of the Chinese Association for Laboratory Animal Sciences(CALAS),and the permanent professor of Chinese Academy of Medical Sciences(CAMS)&Peking Union Medical College(PUMC).Moreover,she is the senior scientist of Institute of Laboratory Animal Sciences(ILAS),CAMS&PUMC.She is also the Vice-President of the Asian Federation of Laboratory Animal Science Associations(AFLAS),a board member of the International Council for Laboratory Animal Science(ICLAS),and Chairman of the National Standardization Technical Committee of Laboratory Animals.In addition to Animal Models and Experimental Medicine,Prof.Qin is also the Editor-in-Chief of Acta Laboratorium Animalis Scientia Sinica and Chinese Journal of Comparative Medicine.
