Volume XLII-2/W7
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 531-535, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-531-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 531-535, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-531-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  12 Sep 2017

12 Sep 2017

BDS/GPS INTEGRATED POSITIONING METHOD RESEARCH BASED ON NONLINEAR KALMAN FILTERING

Y. Ma1, W. Yuan2, and H. Sun1 Y. Ma et al.
  • 1China Academy of Civil Aviation Science and Technology, 100028 Beijing, China
  • 2China Aero Geophysical Survey Remote Sensing Center for Land and Resources (AGRS), 100083 Beijing, China

Keywords: Extended Kalman Filter(EKF), Unscented Kalman Filter(UKF), Particle Filter(PF), Integrated Positioning

Abstract. In order to realize fast and accurate BDS/GPS integrated positioning, it is necessary to overcome the adverse effects of signal attenuation, multipath effect and echo interference to ensure the result of continuous and accurate navigation and positioning. In this paper, pseudo-range positioning is used as the mathematical model. In the stage of data preprocessing, using precise and smooth carrier phase measurement value to promote the rough pseudo-range measurement value without ambiguity. At last, the Extended Kalman Filter(EKF), the Unscented Kalman Filter(UKF) and the Particle Filter(PF) algorithm are applied in the integrated positioning method for higher positioning accuracy. The experimental results show that the positioning accuracy of PF is the highest, and UKF is better than EKF.