TY - JOUR
T1 - 信息融合理论研究进展:基于变分贝叶斯的联合优化
AU - Pan, Quan
AU - Hu, Yu Mei
AU - Lan, Hua
AU - Sun, Shuai
AU - Wang, Zeng Fu
AU - Yang, Feng
N1 - Publisher Copyright:
Copyright © 2019 Acta Automatica Sinica. All rights reserved.
PY - 2019/7
Y1 - 2019/7
N2 - By reviewing the development of information fusion theory in recent years, this paper analyzes the problems of target tracking systems, such as nonlinearity, multi-mode, deep coupling, networking, high-dimensionality and unknown disturbance input, and points out the necessity of joint optimization in target tracking system. Furthermore, several joint optimization methods, including the joint detection and estimation, joint clustering and estimation, joint association and estimation, joint decision and estimation are discussed. Meanwhile, we emphatically introduce the integrated optimization method based on the variational Bayesian theory that provides a unified framework of joint identification and estimation. Taking over-the-horizon radar as an application background, we give a general joint optimization method for the multi-path multi-mode multi-target tracking system in this paper. In addition, future research directions of the variational Bayesian theory in the field of target tracking are discussed.
AB - By reviewing the development of information fusion theory in recent years, this paper analyzes the problems of target tracking systems, such as nonlinearity, multi-mode, deep coupling, networking, high-dimensionality and unknown disturbance input, and points out the necessity of joint optimization in target tracking system. Furthermore, several joint optimization methods, including the joint detection and estimation, joint clustering and estimation, joint association and estimation, joint decision and estimation are discussed. Meanwhile, we emphatically introduce the integrated optimization method based on the variational Bayesian theory that provides a unified framework of joint identification and estimation. Taking over-the-horizon radar as an application background, we give a general joint optimization method for the multi-path multi-mode multi-target tracking system in this paper. In addition, future research directions of the variational Bayesian theory in the field of target tracking are discussed.
KW - Information fusion
KW - Joint optimization
KW - State estimation
KW - Target tracking
KW - Variational Bayesian theory
UR - http://www.scopus.com/inward/record.url?scp=85071509065&partnerID=8YFLogxK
U2 - 10.16383/j.aas.c180029
DO - 10.16383/j.aas.c180029
M3 - 文献综述
AN - SCOPUS:85071509065
SN - 0254-4156
VL - 45
SP - 1207
EP - 1223
JO - Zidonghua Xuebao/Acta Automatica Sinica
JF - Zidonghua Xuebao/Acta Automatica Sinica
IS - 7
ER -