Derivation of the multi-model generalized labeled multi-Bernoulli filter: a solution to multi-target hybrid systems
Weihua Wu, Yichao Cai, Hongbin Jin, Mao Yu Zheng, Xun Feng, Zewen Guan · Frontiers of Information Technology & Electronic Engineering · 2021
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.