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Articles | Volume XLIII-B2-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 59–64, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-59-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 59–64, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B2-2022-59-2022
 
30 May 2022
30 May 2022

IMPACT OF GNSS SIGNAL OUTAGE ON EOPS USING FORWARD KALMAN FILTER AND SMOOTHING ALGORITHM

A. Jouybari1, M. Bagherbandi1,2, and F. Nilfouroushan1,3 A. Jouybari et al.
  • 1Faculty of Engineering and Sustainable Development, University of Gävle, Gävle, Sweden
  • 2Division of Geodesy and satellite positioning, Royal Institute of Technology (KTH), Stockholm, Sweden
  • 3Department of Geodetic Infrastructure, Geodata Division, Lantmäteriet, Gävle, Sweden

Keywords: Tightly Coupled, Forward Kalman Filter, GNSS/IMU Integration, Smoothing Algorithm, Virtual Reference Station, Exterior Orientation Parameters, Differential GNSS processing

Abstract. The global navigation satellite system (GNSS) has been playing the principal role in positioning applications in past decades. Position robustness degrades with a standalone receiver due to GNSS signal outage in mobile mapping systems. The GNSS and inertial measurement unit (IMU) integration is used to solve positioning degradation. This article studies the GNSS/IMU integration processing (i.e., forward Kalman filter (KF) and smoothing algorithm) using a single or a network of nearby GNSS reference stations. In addition, we analyze the impact of simulated GNSS signal outage on exterior orientation parameters (EOPs). The outcomes confirm that the smoothing algorithm works better than the forward KF and improves the accuracy for position and orientation in the case when there is no GNSS signal outage. Also, it improves the position and orientation accuracy by about 95% and 60% when there is a 180 second GNSS signal outage, respectively.