Sigma-Point Kalman Filtering for Tightly Coupled GPS/INS Integration

Yong Li, Chris Rizos, Jinling Wang, Peter Mumford, and Weidong Ding

Peer Reviewed

Abstract: Sigma-point Kalman filtering (SPKF) uses a set of sigma points to completely capture the first and second order moments of the a priori random variable. Using the SPKF, a tightly-coupled GPS/INS integration can be designed in either the navigation state space or the error state space. This paper uses the error state space. This approach blends the INS error model with the nonlinear range and range-rate equations, and can avoid the time-consuming unscented transformation on the strapdown computation which is needed when the implementation occurs through the navigation state space. The SPKF demonstrated its ability to track INS errors in the field test. The comparison between SPKF and EKF was conducted in terms of accuracy and time consumption. The results show that for the pseudorange-based tightly-coupled GPS/INS integration, the SPKF design provides little performance benefit compared to the EKF.
Published in: NAVIGATION, Journal of the Institute of Navigation, Volume 55, Number 3
Pages: 167 - 177
Cite this article: Li, Yong, Rizos, Chris, Wang, Jinling, Mumford, Peter, Ding, Weidong, "Sigma-Point Kalman Filtering for Tightly Coupled GPS/INS Integration", NAVIGATION, Journal of The Institute of Navigation, Vol. 55, No. 3, Fall 2008, pp. 167-177.
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