Derivation of the multi-model generalized labeled multi-Bernoulli filter:a solution to multi-target hybrid systems

查看全文 作　　者：Weihua [1]WU;Yichao [1]CAI;Hongbin [1]JIN;Mao [1]ZHENG;Xun [1]FENG;Zewen [1]GUAN

机构地区：[1]Department of Early Warning Intelligence,Air Force Early Warning Academy,Wuhan 430019,China

出　　处：《Frontiers of Information Technology & Electronic Engineering》索引2021年第22卷第1期,共9页

基　　金：Project supported by the National Natural Science Foundation of China(No.61601510);the Young Talent Support Project of China Association for Science and Technology(No.18-JCJQ-QT-008)。 摘　　要：In this study,we extend traditional(single-target)hybrid systems to multi-target hybrid systems with a focus on the multi-maneuvering-target tracking system.This system consists of a continuous state,a discrete and switchable state,and a discrete,time-constant,and unique state.By defining a new generalized labeled multi-Bernoulli density,we prove that it is closed under the Chapman-Kolmogorov prediction and Bayes update for multi-target hybrid systems.In other words,we provide the exact derivation of a solution to this system,i.e.,the multi-model generalized labeled multi-Bemoulli filter,which has been developed without strict proof. 关键词：Multi-maneuvering-target tracking MULTI-MODEL Generalized labeled multi・Bemoulli filter Multi-target hybrid systems

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Derivation of the multi-model generalized labeled multi-Bernoulli filter:a solution to multi-target hybrid systems

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