Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3/W1, 149-155, 2014
https://doi.org/10.5194/isprsarchives-XL-3-W1-149-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
05 Mar 2014
SINGULAR VALUE DECOMPOSITION-BASED ROBUST CUBATURE KALMAN FILTER FOR AN INTEGRATED GPS/SINS NAVIGATION SYSTEM
Q. Zhang1,2, X. Meng2, S. Zhang1, and Y. Wang1 1School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, 221116, China
2Sino-UK Geospatial Engineering Centre, University of Nottingham, Nottingham, NG7 2TU, UK
Keywords: Singular Value Decomposition, Cubature Kalman Filter, Integrated GNSS/SINS Navigation System, Nonlinear Filter Abstract. A new nonlinear robust filter is proposed in this paper to deal with the outliers of an integrated GPS/SINS navigation system. The influence of different design parameters for H cubature Kalman filter is analysed. It is found that when the design parameter is smaller, the robustness of the filter is stronger. However, the design parameter is easily out of step with the Riccati equation and the filter is easy to diverge. In this respect, the singular value decomposition algorithm is employed to replace Cholesky decomposition in the robust cubature Kalman filter. On the wider conditions for design parameter, the new filter is more robust. The testing results demonstrate that the proposed filter algorithm is more reliable and effective in dealing the data sets produced by the integrated GPS/SINS system.
Conference paper (PDF, 515 KB)


Citation: Zhang, Q., Meng, X., Zhang, S., and Wang, Y.: SINGULAR VALUE DECOMPOSITION-BASED ROBUST CUBATURE KALMAN FILTER FOR AN INTEGRATED GPS/SINS NAVIGATION SYSTEM, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3/W1, 149-155, https://doi.org/10.5194/isprsarchives-XL-3-W1-149-2014, 2014.

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