Square-root quadrature Kalman filtering

被引:116
作者
Arasaratnam, Ienkaran [1 ]
Haykin, Simon [1 ]
机构
[1] McMaster Univ, Cognit Syst Lab, Hamilton, ON L8S 4K1, Canada
关键词
matrix triangularization; quadrature Kalman filter (QKF); quadrature rule; square-root filter;
D O I
10.1109/TSP.2007.914964
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The quadrature Kalman filter (QKF) is a recursive, non-linear filtering algorithm developed in the Kalman filtering framework. It computes the mean and covariance of all conditional densities using the Gauss-Hermite quadrature rule. In this correspondence, we develop a square-root extension of the quadrature Kalman filter using matrix triangularizations. The square-root quadrature Kalman filter (SQKF) propagates the mean and the square root of the covariance. Although equivalent to the QKF algebraically, the SQKF exhibits excellent numerical characteristics, but at the expense of increased computational complexity. We also present possible refinements of the generic SQKF.
引用
收藏
页码:2589 / 2593
页数:5
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