Transformed Unscented Kalman Filter

被引:145
作者
Chang, Lubin [1 ]
Hu, Baiqing [1 ]
Li, An [1 ]
Qin, Fangjun [1 ]
机构
[1] Naval Univ Engn, Dept Nav Engn, Wuhan 430033, Peoples R China
基金
中国国家自然科学基金;
关键词
Cubature Kalman filter; nonlocal sampling problem; numerical integration formulas; orthogonal transformation; unscented Kalman filter;
D O I
10.1109/TAC.2012.2204830
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This technical note concerns the deterministic sampling points construction strategy for unscented Kalman filter (UKF) and cubature Kalman filter (CKF). From the numerical-integration viewpoint, a new deterministic sampling points set is derived by orthogonal transformation on the cubature points. By embedding these points into the UKF framework, a modified nonlinear filter named transformed unscented Kalman filter (TUKF) is derived. The TUKF can address the nonlocal sampling problem inherent in CKF while maintaining the virtue of numerical stability for high dimensional problems. Moreover, the methodology proposed in this technical note can be used to construct nonlinear filters with improved accuracy for certain problems. The performance of the proposed algorithm is demonstrated through a nonlinear high dimensional problem.
引用
收藏
页码:252 / 257
页数:7
相关论文
共 15 条
[1]   Cubature Kalman Filters [J].
Arasaratnam, Ienkaran ;
Haykin, Simon .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2009, 54 (06) :1254-1269
[2]  
Gustafsson F., 2008, P IEEE INT C AC SPEE
[3]   Some Relations Between Extended and Unscented Kalman Filters [J].
Gustafsson, Fredrik ;
Hendeby, Gustaf .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2012, 60 (02) :545-555
[4]   Gaussian filters for nonlinear filtering problems [J].
Ito, K ;
Xiong, KQ .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2000, 45 (05) :910-927
[5]   A new method for the nonlinear transformation of means and covariances in filters and estimators [J].
Julier, S ;
Uhlmann, J ;
Durrant-Whyte, HF .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2000, 45 (03) :477-482
[6]   Unscented filtering and nonlinear estimation [J].
Julier, SJ ;
Uhlmann, JK .
PROCEEDINGS OF THE IEEE, 2004, 92 (03) :401-422
[7]  
Julier SJ, 2002, P AMER CONTR CONF, V1-6, P4555, DOI 10.1109/ACC.2002.1025369
[8]  
LERNER U, 2002, THESIS STANFORD U ST
[9]   A derivative-free implementation of the extended Kalman filter [J].
Quine, Brendan M. .
AUTOMATICA, 2006, 42 (11) :1927-1934
[10]  
Sarkka S., 2011, BAYESIAN ESTIMATION