Abstract

The occlusion of buildings in urban environments leads to the intermittent reception of satellite signals, which limits the utilization of observations. This subsequently results in a decline of the positioning and attitude accuracy of Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS) integrated system (GNSS/INS). This study implements a smooth post-processing strategy based on a tightly coupled differential GNSS/INS. Specifically, this strategy used the INS-estimated position to reinitialize integer ambiguity. The GNSS raw observations were input into the Kalman filter to update the measurement. The Rauch–Tung–Striebel smoothing (RTSS) algorithm was used to process the observations of the entire period. This study analyzed the performance of loosely coupled and tightly coupled systems in an urban environment and the improvement of the RTSS algorithm on the navigation solution from the perspective of fully mining the observations. The experimental results of the simulation data and real data show that, compared with the traditional tightly coupled processing strategy which does not use INS-aided integer ambiguity resolution and RTSS algorithm, the strategy in this study sufficiently utilized INS observations and GNSS observations to effectively improve the accuracy of positioning and attitude and ensure the continuity of navigation results in an obstructed environment.

Highlights

  • With the development of the geospatial information service industry, the demand for rapid and accurate geospatial information access has increased

  • The results show that the proposed strategy can effectively the pose accuracy even during the intermittent reception of satellite signals

  • The split closed-loop fiber optic integrated navigation system SPAN-LCI manufactured by NovAtel (Figure 3) was used in the experiment, which contained a Global Navigation Satellite System (GNSS) receiver and an inertial measurement unit (IMU)-LCI tactical fiber IMU

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Summary

Introduction

With the development of the geospatial information service industry, the demand for rapid and accurate geospatial information access has increased. GNSS/INS integration is typically applied in urban environments, which are extremely complex, with dense high-rise buildings, viaducts, tunnels, and other infrastructure. The most typical environment is the urban canyon, which is formed by dense building blocks and tall trees. In this environment, the GNSS signal suffers frequent lock loss, and the existing observation data are not fully utilized and do not meet the demand for high-precision positioning and pose determination. The GNSS signal suffers frequent lock loss, and the existing observation data are not fully utilized and do not meet the demand for high-precision positioning and pose determination

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