基于UKF算法的单观测站目标跟踪研究

2021 IEEE 9th International Conference on Information, Communication and Networks (ICICN) Pub Date : 2021-11-25 DOI:10.1109/icicn52636.2021.9673925

Lieping Zhang, Mingyang Tan, Yanlin Yu, Shenglan Zhang, Wei Liu, Zuqiong Zhang

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引用次数: 0

摘要

针对单观测站目标跟踪问题，研究了基于Unscented卡尔曼滤波(UKF)的单观测站目标跟踪算法。本文首先分析了UKF算法，重点研究了UKF算法的实现。在此基础上，给出了单观测站目标跟踪的建模原理，提出了基于UKF算法的单观测站目标跟踪算法。最后，利用MATLAB进行仿真实验。仿真结果表明，与扩展卡尔曼滤波算法相比，基于UKF的目标跟踪算法具有更高的跟踪精度，但耗时较长。

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Research on Single Observation Station Target Tracking Based on UKF Algorithm

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.

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2021 IEEE 9th International Conference on Information, Communication and Networks (ICICN)

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