IMM Algorithm Based on H∞ Filter for Maneuvering Target Tracking

被引：0
作者：
Liu, Meiqin [1 ,2 ]
Fan, Zhen [2 ]
Wang, Xie [2 ]
Zhang, Senlin [2 ]
机构：
[1] Zhejiang Univ, State Key Lab Ind Control Technol, Hangzhou 310027, Zhejiang, Peoples R China
[2] Zhejiang Univ, Coll Elect Engn, Hangzhou 310027, Zhejiang, Peoples R China
来源：
PROCEEDINGS OF THE 36TH CHINESE CONTROL CONFERENCE (CCC 2017) | 2017年
基金：
中国国家自然科学基金;
关键词：
State Estimation; Noise Statistics Estimate; H-infinity Filter; Interacting Multiple Model Algorithm; Target Tracking; NOISE; COVARIANCE; SYSTEMS; FUSION;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Correct knowledge of noise statistics is essential for an effective estimator in maneuvering target tracking. In practice, however, the noise statistics are usually unknown or not perfectly known. To deal with the estimation problem in linear discrete-time systems with Markov jump parameters, where the measurement noise covariance is unknown, a novel approach is presented in this paper. This approach is based on the interacting multiple model (IMM) framework. An H-infinity filter is employed to construct a noise statistics estimator to obtain the information which is necessary for the IMM algorithm. In our approach, even the priori knowledge of noise statistics is not needed. The noise statistics loss problem is solved while the merits of IMM algorithm is reserved. The effectiveness of the proposed approach is demonstrated in comparison with single-model H-infinity filter through Monte Carlo simulation for maneuvering target tracking.
引用
收藏
页码：5385 / 5391
页数：7
相关论文
共 23 条
[21]   Game theory approach to discrete H-infinity filter design [J].
Shen, XM ;
Deng, L .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1997, 45 (04) :1092-1095
[22]  
Simon D, 2006, OPTIMAL STATE ESTIMA
[23]   A TRANSFER-FUNCTION APPROACH TO THE PROBLEMS OF DISCRETE-TIME-SYSTEMS - H-INFINITY-OPTIMAL LINEAR-CONTROL AND FILTERING [J].
YAESH, I ;
SHAKED, U .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1991, 36 (11) :1264-1271
123