Accuracy Enhancement of GNSS/INS Positioning in Dense Urban Environments with NLOS Signal Rejection based on Geometric Model

Abstract

In this paper, we propose a NLOS (Non-Line-Of-Sight) signal rejection method to improve the positioning accuracy of integrated GNSS (Global Navigation Satellite System) and INS (Inertial Navigation System) system for a vehicle in dense urban environments. NLOS signals caused by reflection and diffraction always have positive measurement errors in pseudo-ranges, and they should be excluded in the Kalman filter of GNSS/INS, because the filter assumes that the measurement errors are zero-mean. In the proposed method, the positive errors in pseudo-ranges are geometrically estimated by simplifying the environments around a vehicle, and the signal that is supposed to be a NLOS signal based on the estimated errors is excluded from the measurements of the Kalman filter. We apply the proposed method to the measurement data obtained by actual driving in dense urban environments, and demonstrate that the positioning accuracy is improved by the proposed method.