State Estimation based Adaptive Extended Kalman Filter for Moving Object Tracking with Angle-only Measurements

被引：0

作者：

Doan Van Thuy ^{[1
]}

Belov, Mikhail P. ^{[2
]}

Tran Huu Phuong ^{[2
]}

机构：

[1] Inst Sci & Technol, Inst Automat, Hanoi, Vietnam

[2] St Petersburg Electrotech Univ LETI, Dept Robot & Ind Automat, St Petersburg, Russia

来源：

PROCEEDINGS OF THE 2021 IEEE CONFERENCE OF RUSSIAN YOUNG RESEARCHERS IN ELECTRICAL AND ELECTRONIC ENGINEERING (ELCONRUS) | 2021年

关键词：

adaptive extended Kalman filter; moving object tracking; observer-moving object engagement; angle-only measurements;

D O I：

10.1109/ElConRus51938.2021.9396317

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This article deals with an application of adaptive extended Kalman filter for state estimation in moving object tracking problem with angle-only measurements. The nonlinear two-dimensional model of observer-moving object engagement in modified polar coordinates is described with taking maneuver of moving object into consideration. The next section presents the mathematical approach to synthesize algorithm of both extended Kalman and adaptive extended Kalman filters for nonlinear state estimation. In this work, designing and testing of state filters are carried out in MATLAB/Simulink environment. The simulation results indicate that the proposed adaptive extended Kalman filter improves accuracy and stability of estimated parameters of moving object tracking in compare with extended Kalman filter.

引用

页码：866 / 869

页数：4

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