Title :
Comparison of the sparse-grid quadrature rule and the cubature rule in nonlinear filtering
Author :
Bin Jia ; Ming Xin ; Yang Cheng
Author_Institution :
Dept. of Electr. Eng., Columbia Univ., New York, NY, USA
Abstract :
In this paper, the recently developed sparse-grid quadrature filter is compared with the cubature Kalman filter. The relation between the sparse-grid quadrature rule and the cubature rule is revealed. It can be shown that arbitrary degree cubature rules can be obtained by the projection of the sparse-grid quadrature rule. Since both rules can achieve an arbitrary high degree of accuracy, they are more accurate than the conventional third-degree cubature rule and the unscented transformation. In addition, they are computationally more efficient than the Gauss-Hermite quadrature rule and the Monte-Carlo method when they are used to calculate the Gaussian type integrals in the nonlinear filtering. The comparison of these rules is demonstrated by a benchmark numerical integration example.
Keywords :
Gaussian processes; integral equations; nonlinear filters; Gaussian type integral; arbitrary degree cubature rule; nonlinear filtering; numerical integration; sparse-grid quadrature filter; sparse-grid quadrature rule; Accuracy; Approximation methods; Filtering; Gaussian approximation; Integral equations; Polynomials;
Conference_Titel :
Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
Conference_Location :
Maui, HI
Print_ISBN :
978-1-4673-2065-8
Electronic_ISBN :
0743-1546
DOI :
10.1109/CDC.2012.6426393