Iterative Unbiased Converted Measurement Kalman Filter for Target Tracking

被引：3
作者：
Li, Da [1 ,2 ]
Zou, Xiangyu [1 ,2 ]
Li, Ruifang [1 ,2 ]
机构：
[1] Wuhan Univ Technol, Sch Informat Engn, Wuhan 430070, Hubei, Peoples R China
[2] Wuhan Univ Technol, Key Lab Fiber Opt Sensing Technol & Informat Proc, Minist Educ, Wuhan 430070, Hubei, Peoples R China
来源：
2017 10TH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID), VOL. 1 | 2017年
基金：
中国国家自然科学基金;
关键词：
iteration method; Kalman filter; target tracking; unbiased converted measurement;
D O I：
10.1109/ISCID.2017.52
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
It is important to develop a robust and fast tracking algorithm for modern tracking system because the target moves more and more fast. Therefore, a novel algorithm named the iterative unbiased converted measurement Kalman filter (IUCMKF) is proposed based on the analysis and comparison of conventional target tracking methods. The new algorithm is developed from unbiased converted measurement Kalman filter, but it can obtain more accurate state and covariance estimation. Compared with the existing target tracking approaches, the proposed method has potential advantages in tracking accuracy. The correctness as well as validity of the algorithm is demonstrated through numerical simulation results.
引用
收藏
页码：342 / 345
页数：4
相关论文
共 50 条
[41]   A suboptimal fading quadrature Kalman filter for target tracking [J].
Liu, Zhao ;
Feng, Xin-xi ;
Kong, Yun-bo ;
Xu, Rui-yang .
WIRELESS COMMUNICATION AND SENSOR NETWORK, 2016, :836-848
[42]   Cascaded Kalman filter for target tracking in automotive radar [J].
Li, Yang ;
Liang, Can ;
Lu, Man ;
Hu, Xueyao ;
Wang, Yanhua .
JOURNAL OF ENGINEERING-JOE, 2019, 2019 (19) :6264-6267
[43]   A Survey of Maneuvering Target Tracking Using Kalman Filter [J].
Li, Zhongmin ;
Wu, Haochen .
PROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON MECHATRONICS, MATERIALS, CHEMISTRY AND COMPUTER ENGINEERING 2015 (ICMMCCE 2015), 2015, 39 :542-545
[44]   Target Tracking Algorithm Based on Meanshift and Kalman Filter [J].
Li H. ;
Zhu J. .
Journal of Beijing Institute of Technology (English Edition), 2019, 28 (02) :365-370
[45]   Target Tracking Based on Extended Kalman Particle Filter [J].
Liu ChongYi ;
Fu LinYu ;
Lu Cheng ;
Yang JingTing .
PROCEEDINGS OF 2017 3RD IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND COMMUNICATIONS (ICCC), 2017, :1715-1719
[46]   Target Tracking Algorithm Based on Meanshift and Kalman Filter [J].
Hua Li ;
Jia Zhu .
Journal of Beijing Institute of Technology, 2019, 28 (02) :365-370
[47]   Application of Unscented Kalman Filter for Flying Target Tracking [J].
Yan, Honglei ;
Huang, Genghua ;
Wang, Haiwei ;
Shu, Rong .
2013 INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CLOUD COMPUTING (ISCC), 2014, :61-66
[48]   A HYBRID KALMAN/ΓH∞ FILTER FOR MANEUVERING TARGET TRACKING [J].
Kemouche, M. S. ;
Aouf, N. ;
Tsourdos, A. ;
White, B. .
ICSPC: 2007 IEEE INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATIONS, VOLS 1-3, PROCEEDINGS, 2007, :1267-+
[49]   Adaptive Kalman Filter for Target Tracking in the UWB Networks [J].
Domuta, Ioan ;
Palade, Tudor Petru .
PROCEEDINGS OF THE 2016 13TH WORKSHOP ON POSITIONING, NAVIGATION AND COMMUNICATIONS (WPNC), 2016,
[50]   A Comprehensive Study of Kalman Filter and Extended Kalman Filter for Target Tracking in Wireless Sensor Networks [J].
Di, Ma ;
Joo, Er Meng ;
Beng, Lim Hock .
2008 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC), VOLS 1-6, 2008, :2791-+
12345