Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2, 127-132, 2014
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-2/127/2014/
doi:10.5194/isprsarchives-XL-2-127-2014
© Author(s) 2014. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
11 Nov 2014
Non-Linear Filtering for Precise Point Positioning GPS/INS integration
M. Abd Rabbou and A. El-Rabbany Department of Civil Engineering, Ryerson University, 350 Victoria Street, Toronto, Ontario, M5B 2K3, Canada
Keywords: GPS, PPP, INS, EKF, UKF, PF and tightly coupled Abstract. This research investigates the performance of non-linear estimation filtering for GPS-PPP/MEMS-based inertial system. Although integrated GPS/INS system involves nonlinear motion state and measurement models, the most common estimation filter employed is extended Kalman filter. In this paper, both unscented Kalman filter and particle filter are developed and compared with extended Kalman filter. Tightly coupled mechanization is adopted, which is developed in the raw measurements domain. Un-differenced ionosphere-free linear combination of pseudorange and carrier-phase measurements is employed. The performance of the proposed non-linear filters is analyzed using real test scenario. The test results indicate that comparable accuracy-level are obtained from the proposed filters compared with extended Kalman filter in positioning, velocity and attitude when the measurement updates from GPS measurements are available.
Conference paper (PDF, 1010 KB)


Citation: Abd Rabbou, M. and El-Rabbany, A.: Non-Linear Filtering for Precise Point Positioning GPS/INS integration, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2, 127-132, doi:10.5194/isprsarchives-XL-2-127-2014, 2014.

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