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

FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING(2021)

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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-Bernoulli filter, which has been developed without strict proof.
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关键词
Multi-maneuvering-target tracking, Multi-model, Generalized labeled multi-Bernoulli filter, Multi-target hybrid systems, TP391, TN953
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