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

doi:10.1631/FITEE.2000105

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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

复杂网络和系统的分布式滤波与控制专辑 | Updated：2022-05-19

- 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
  Enhanced Publication
- Derivation of the multi-model generalized labeled multi-Bernoulli filter: a solution to multi-target hybrid systems
- 信息与电子工程前沿（英文） 2021年22卷第1期页码：79-87
- Affiliations：
  
  Department of Early Warning Intelligence, Air Force Early Warning Academy, Wuhan 430019, China
- Author bio：
  
  Weihua WU, E-mail: weihuawu1987@163.com
- Funds：
  
  Project supported by the National Natural Science Foundation of China (No. 61601510) and the Young Talent Support Project of China Association for Science and Technology (No. 18-JCJQ-QT-008)
- DOI：10.1631/FITEE.2000105
  中图分类号： TP391;TN953
- 纸质出版日期：2021-01，
  
  收稿日期：2020-03-11，
  
  修回日期：2020-09-11，
- Accepted：
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吴卫华, 蔡益朝, 金宏斌, 等. 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[J]. 信息与电子工程前沿（英文）, 2021,22(1):79-87.

WU WEIHUA, CAI YICHAO, JIN HONGBIN, et al. Derivation of the multi-model generalized labeled multi-Bernoulli filter: a solution to multi-target hybrid systems. [J]. Frontiers of information technology & electronic engineering, 2021, 22(1): 79-87.
吴卫华, 蔡益朝, 金宏斌, 等. 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[J]. 信息与电子工程前沿（英文）, 2021,22(1):79-87. DOI： 10.1631/FITEE.2000105.

WU WEIHUA, CAI YICHAO, JIN HONGBIN, et al. Derivation of the multi-model generalized labeled multi-Bernoulli filter: a solution to multi-target hybrid systems. [J]. Frontiers of information technology & electronic engineering, 2021, 22(1): 79-87. DOI： 10.1631/FITEE.2000105.

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。

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.

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

Keywords

Multi-maneuvering-target trackingMulti-modelGeneralized labeled multi-Bernoulli filterMulti-target hybrid systems

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