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Frontiers of Information Technology & Electronic Engineering
ISSN 2095-9184 (print), ISSN 2095-9230 (online)
2021 Vol.22 No.1 P.79-87
Derivation of the multi-model generalized labeled multi-Bernoulli filter: a solution to multi-target hybrid systems
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.
Key words: Multi-maneuvering-target tracking, Multi-model, Generalized labeled multi-Bernoulli filter, Multi-target hybrid systems
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。
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DOI:
10.1631/FITEE.2000105
CLC number:
TP391; TN953
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On-line Access:
2021-01-11
Received:
2020-03-11
Revision Accepted:
2020-06-30
Crosschecked:
2020-09-11