Open AccessComparative Study on Application of Extended Kalman Filter and Unscented Kalman Filter in Target Tracking
Author(s) -
Xiao-Tong Hu Xiao-Fei Deng,
Si-Qi Zhao Qin Guo Cui-Xia Zeng,
Kailiang Zhou
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/864/1/012055
Subject(s) - unscented transform , fast kalman filter , kalman filter , alpha beta filter , invariant extended kalman filter , extended kalman filter , ensemble kalman filter , control theory (sociology) , computer science , tracking (education) , moving horizon estimation , artificial intelligence , psychology , control (management) , pedagogy
This paper mainly describes the basic principles of extended Kalman filter and unscented Kalman filter and the application of them in target tracking based on observation distance At last the two algorithms are compared by Matlab software The simulation results show that unscented Kalman filter has better matching effect than extended Kalman filter and the former has smaller error variation and better convergence than the latter