Interacting multiple model unscented Kalman filter

被引：0
|
作者：
Feng, Yang [1 ]
Quan, Pan [1 ]
Yan, Liang [1 ]
Liang, Ye [1 ]
机构：
[1] Northwestern Polytech Univ, Coll Automat, Xian 710072, Peoples R China
来源：
Proceedings of the 24th Chinese Control Conference, Vols 1 and 2 | 2005年
关键词：
interacting multiple model; unscented Kalman filter; maneuvering target tracking; nonlinear estimation;
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：
Interacting multiple model (IMM) estimator is one of the most effective methods for maneuvering target tracking. In practical applications, target tracking often does as a nonlinear estimation problem. Linearization of filter model should be done if IMM is used in nonlinear estimation. Interacting multiple model unscented Kalman filter (IMMUKF) is presented for nonlinear maneuvering target tracking. IMMUKF possesses the merits of IMM for maneuvering target tracking and UKF for nonlinear estimation. Simulation is presented to evaluate the performance of the algorithm. Compared with IMMEKF, the new method gets better performance.
引用
收藏
页码：314 / 317
页数：4
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