Joint sigma-point Kalman filter based bearing-only tracking

被引：0
|
作者：
Hou, Daiwen [1 ]
Yin, Fuliang [1 ]
Zhang, Liyan [1 ]
机构：
[1] Dalian Univ Technol, Sch Elect & Informat Engn, Dalian 116023, Peoples R China
来源：
WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS | 2006年
关键词：
bearing-only tracking; systematic error; Kalman filter; sigma-point transformation;
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：
These instructions give you the basic guidelines for preparing papers for WCICA/IEEE conference proceedings. Abstract - A novel joint sigma-point Kalman filter algorithm is proposed to solve the problems of slow convergence rate and biased state estimation when systematic error exists in bearing-only target tracking. The algorithm can eliminate the effect of systematic error to the state estimation as well as reduce linearization error. The simulation results demonstrate the validity of the proposed algorithm.
引用
收藏
页码：944 / 948
页数：5
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