Maneuvering target tracking by adaptive statistics model

作     者：JIN Xue-bo DU Jing-jing BAO Jia 

作者机构：College of Computer and Information Engineering Beijing Technology and Business University College of Informatics Zhejiang Sci-Tech University 

出 版 物：《The Journal of China Universities of Posts and Telecommunications》 (中国邮电高校学报（英文版）)

年 卷 期：2013年第20卷第1期

页      面：108-114页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 0839[工学-网络空间安全] 08[工学] 081105[工学-导航、制导与控制] 081001[工学-通信与信息系统] 081002[工学-信号与信息处理] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程] 

基　　金：supported by the National Natural Science Foundation of China (61273002  60971119) 

主　　题：maneuvering target target model statistics relation state estimation 

摘      要：A good model can extract useful information about the target＇s state from observations effectively. There are many models used to tracking a, maneuvering target such as constant-velocity （CV） model, Singer acceleration model （zero-mean first-order Markov model） and current model （mean-adaptive acceleration model）, etc. While due to the complexity of maneuvering target, to seek the target model which can get better performance is still a subject worthy of study. Based on statistics relation between the autocormlation function and the covariance of Markov random processing, this paper develops a model which can adaptively adjust system parameters on line. Simulations show the good estimation performance get by the model developed here, and comparing CV, Singer and current models, the model can adaptively get the model parameter while tracking the trajectory and needn＇t doing several tests to obtain a priori parameter.