Research on Single Observation Station Target Tracking Based on UKF Algorithm

被引：1

作者：

Zhang, Lieping ^{[1
]}

Tan, Mingyang ^{[1
]}

Yu, Yanlin ^{[1
]}

Zhang, Shenglan ^{[2
]}

Liu, Wei ^{[2
]}

Zhang, Zuqiong ^{[2
]}

机构：

[1] Guilin Guilin Univ Technol, Coll OfMech & Control Engn, Guilin, Peoples R China

[2] Guilin Guilin Univ Technol, Network & Informat Ctr, Guilin, Peoples R China

来源：

2021 IEEE 9TH INTERNATIONAL CONFERENCE ON INFORMATION, COMMUNICATION AND NETWORKS (ICICN 2021) | 2021年

基金：

中国国家自然科学基金;

关键词：

single observation station; target tracking; extend kalman filter; unscented kalman filter; experimental simulation;

D O I：

10.1109/ICICN52636.2021.9673925

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Aiming at the problem of single observation station target tracking, this paper studies the single observation station target tracking algorithm based on Unscented Kalman filter (UKF). Firstly, this paper analyzes the UKF algorithm, and focuses on the implementation of UKF algorithm. On this basis, the modeling principle of single observation station target tracking is given, and the single observation station target tracking algorithm based on UKF algorithm is proposed. Finally, the simulation experiment is carried out by MATLAB. The simulation results show that, compared with the extended Kalman filter algorithm, the target tracking algorithm based on UKF has higher tracking accuracy, but takes longer time.

引用

页码：52 / 57

页数：6

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