@inproceedings{416e00bf37344eafa2fcac3403f84dd3,
title = "An adaptive maneuvering target tracking algorithm based on three-dimensional parameter identification model",
abstract = "An adaptive maneuvering target tracking algorithm based on three-dimensional parameter identification model is put forward to solve three-dimensional maneuvering target tracking problem. Firstly a three-dimensional model parameter identification model is established. Then the extended state observer (ESO) and fading memory least squares method are applied to identify the model parameters. Finally combining the model with converted measurement Kalman filter (CMKF), we achieve an adaptive target tracking algorithm. 100 times of Monte Carlo simulation prove that the algorithm has higher model parameter identification accuracy for different motion modes. It is showed that this algorithm has good filtering performance for three-dimensional maneuvering target tracking in simulation examples.",
keywords = "Three-dimensional parameter identification model, converted measurement Kalman filter, extended state observer, fading memory of least squares",
author = "Yanxuan Wu and Jianbin Chen",
note = "Publisher Copyright: {\textcopyright} 2015 Technical Committee on Control Theory, Chinese Association of Automation.; 34th Chinese Control Conference, CCC 2015 ; Conference date: 28-07-2015 Through 30-07-2015",
year = "2015",
month = sep,
day = "11",
doi = "10.1109/ChiCC.2015.7260496",
language = "English",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "5479--5483",
editor = "Qianchuan Zhao and Shirong Liu",
booktitle = "Proceedings of the 34th Chinese Control Conference, CCC 2015",
address = "United States",
}