JZUS - Journal of Zhejiang University SCIENCE

Frontiers of Information Technology & Electronic Engineering 2021 Vol.22 No.1 P.79-87

http://doi.org/10.1631/FITEE.2000105

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

Author(s): Weihua Wu, Yichao Cai, Hongbin Jin, Mao Zheng, Xun Feng, Zewen Guan
Affiliation(s): Department of Early Warning Intelligence, Air Force Early Warning Academy, Wuhan 430019, China
Corresponding email(s): weihuawu1987@163.com
Key Words: Multi-maneuvering-target tracking, Multi-model, Generalized labeled multi-Bernoulli filter, Multi-target hybrid systems

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Abstract: 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.

多模型广义标签多伯努利滤波器的推导：多目标混合系统解决方案

吴卫华，蔡益朝，金宏斌，郑茂，冯讯，关泽文
空军预警学院预警情报系，中国武汉市，430019

摘要：本文将传统（单目标）混合系统扩展到多目标混合系统，重点研究多机动目标跟踪系统。该系统由连续状态，离散可切换状态以及离散、时不变且唯一性状态组成。通过定义一个新的广义标签多伯努利密度，我们证明对于多目标混合系统，它在查普曼-柯尔莫哥洛夫（Chapman-Kolmogorov）预测和贝叶斯更新下是闭合的。换言之，我们严格推导了多目标混合系统的解决方案，即多模型广义标签多伯努利滤波器--该滤波器虽已被开发，但此前并未得到严格证明。

关键词：多机动目标跟踪；多模型；广义标签多伯努利滤波器；多目标混合系统

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