Fusion of Gaussian Mixture Models for Maneuvering Target Tracking in the Presence of Unknown Cross-correlation  

作　　者：ZHU Hongyan GUO Kai CHEN Shuo 

机构地区：[1]School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China [2]China Electronics Technology Group Corporation No.28 Research Institute, Nanjing 210007, China

出　　处：《Chinese Journal of Electronics》2016年第2期270-276,共7页电子学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(No.61203220);the National Basic Research Program of China(973 Program)(No.2013CB329405)

摘　　要：The paper addresses the problem of estimation fusion for maneuvering target tracking in the presence of unknown cross-correlation. To improve the fusion accuracy, two major points are concerned. Firstly, the Interacting multiple model(IMM) estimator is performed for each sensor, and the local estimate is represented by a Gaussian mixture model instead of a Gaussian density to keep more details of the local tracker. Next, a close-formed solution of fusing two Gaussian mixtures in the Covariance intersection(CI) framework is derived to cope with the unknown cross-correlation of local estimation errors. Experimental results demonstrate that the proposed approach provides some improvements in the fusion accuracy over the competitive methods.The paper addresses the problem of estimation fusion for maneuvering target tracking in the presence of unknown cross-correlation. To improve the fusion accuracy, two major points are concerned. Firstly, the Interacting multiple model（IMM） estimator is performed for each sensor, and the local estimate is represented by a Gaussian mixture model instead of a Gaussian density to keep more details of the local tracker. Next, a close-formed solution of fusing two Gaussian mixtures in the Covariance intersection（CI） framework is derived to cope with the unknown cross-correlation of local estimation errors. Experimental results demonstrate that the proposed approach provides some improvements in the fusion accuracy over the competitive methods.

关 键 词：Gaussian mixture model（GMM） Estimation fusion Interacting multiple model（IMM） Covariance intersection（CI） Cross-correlation 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]