An Adaptive Unscented Kalman Filtering Algorithm for MEMS/GPS Integrated Navigation Systems

被引：5

作者：

Cheng, Jianhua ^{[1
,2
]}

Chen, Daidai ^{[1
]}

Landry, Rene Jr ^{[2
]}

Zhao, Lin ^{[1
]}

Guan, Dongxue ^{[1
]}

机构：

[1] Harbin Engn Univ, Marine Nav Res Inst, Coll Automat, Harbin 150001, Peoples R China

[2] Univ Quebec, Ecole Technol Super, LASSENA Lab, Montreal, PQ H3C 1K3, Canada

来源：

JOURNAL OF APPLIED MATHEMATICS | 2014年

关键词：

INS/GPS;

D O I：

10.1155/2014/451939

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

MEMS/GPS integrated navigation system has been widely used for land-vehicle navigation. This system exhibits large errors because of its nonlinear model and uncertain noise statistic characteristics. Based on the principles of the adaptive Kalman filtering (AKF) and unscented Kalman filtering (AUKF) algorithms, an adaptive unscented Kalman filtering (AUKF) algorithm is proposed. By using noise statistic estimator, the uncertain noise characteristics could be online estimated to adaptively compensate the time-varying noise characteristics. Employing the adaptive filtering principle into UKF, the nonlinearity of system can be restrained. Simulations are conducted for MEMS/GPS integrated navigation system. The results show that the performance of estimation is improved by the AUKF approach compared with both conventional AKF and UKF.

引用

页数：8

共 50 条

[41] A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation
Jiang, Chen
Zhang, Shu-Bi
Zhang, Qiu-Zhao
[J]. SENSORS, 2016, 16 (12):
[42] Adaptive fusion filtering algorithm and its application for INS/GPS integrated navigation system
Wang X.-X.
Zhao L.
[J]. Yuhang Xuebao/Journal of Astronautics, 2010, 31 (11): : 2503 - 2511
[43] A new two-step adaptive robust Kalman filtering in GPS/INS integrated navigation system
Wu, Fumei
Yang, Yuanxi
[J]. Cehui Xuebao/Acta Geodaetica et Cartographica Sinica, 2010, 39 (05): : 522 - 527
[44] Adaptive Kalman Filter for INS/GPS Integrated Navigation System
Xu, Tianlai
[J]. INDUSTRIAL INSTRUMENTATION AND CONTROL SYSTEMS II, PTS 1-3, 2013, 336-338 : 332 - 335
[45] Sigma-point Kalman filtering for integrated GPS and inertial navigation
Crassidis, John L.
[J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2006, 42 (02) : 750 - 756
[46] Fuzzy neural network aided adaptive Kalman filtering for GPS navigation
Jwo, DJ
Huang, HC
[J]. INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS, VOL 1-4, PROCEEDINGS, 2005, : 3859 - 3865
[47] Adaptive fuzzy strong tracking extended kalman filtering for GPS navigation
Jwo, Dah-Jing
Wang, Sheng-Hung
[J]. IEEE SENSORS JOURNAL, 2007, 7 (5-6) : 778 - 789
[48] Fuzzy Adaptive Interacting Multiple Model Unscented Kalman Filter for Integrated Navigation
Jwo, Dah-Jing
Tseng, Chien-Hao
[J]. 2009 IEEE CONTROL APPLICATIONS CCA & INTELLIGENT CONTROL (ISIC), VOLS 1-3, 2009, : 1684 - 1689
[49] Adaptive Federal Kalman Filtering for SINS/GPS Integrated System
杨勇
缪玲娟
[J]. Journal of Beijing Institute of Technology, 2003, (04) : 371 - 375
[50] Development of an Adaptive Unscented Particle Filter for Tightly-coupled MEMS-INS/GPS Integrated Navigation System
Zhou, Junchuan
Knedlik, Stefan
Loffeld, Otmar
[J]. PROCEEDINGS OF THE 2010 INTERNATIONAL TECHNICAL MEETING OF THE INSTITUTE OF NAVIGATION - ITM 2010, 2010, : 31 - 42

← 1 2 3 4 5 →