Using Multiple GNSS Constellations with Strict Quality Constraints for More Accurate Positioning in Urban Environments

摘要

Combined multi-global navigation satellite system (GNSS) signals are capable of improving satellite availability for both standalone and differential positioning. Currently, the potential for highaccuracy automobile navigation using GNSS is constrained by severe multipath and poor satellite geometry, especially in “urban canyons” in large cities. With differential GNSS (D-GNSS) positioning, inconvenient system time differences can be removed by reference-station processing, allowing a user’s receiver position to be accurately calculated using four or more visible satellite signals. Therefore, in the future, we can filter numerous multi-GNSS measurements based on their quality in order to enhance the positioning performance in urban environments. In this paper, we present several methods that use multi-GNSS to filter signals from satellites containing severe multipath errors. In addition, we select single-frequency code-based D-GNSS because it has significant potential due to its low cost and robustness. The first method uses the measured carrier-to-noise ratio (C/N0). When only reflected signals are received in dense urban areas, the C/N0 will decrease by more than 6 dB-Hz, with the exception of high-elevation satellites. Thus, by comparing the measured and expected C/N0 at various elevation angles, we may be able to detect the presence of severe multipath signals. The second method involves using the error residual from the Receiver Autonomous Integrity Monitoring (RAIM), which is a well-known technique for checking the quality of measurements. Signals having severe multipath effects result in significant deterioration of measurements. In addition to the above methods, we introduce several points that should be noted in order to improve D-GNSS. To evaluate our proposed method, we perform positioning tests using a car in an urban environment. Differential positioning was used for multi-GNSS with GPS, QZSS, BeiDou, and GLONASS. We present an evaluation of each technique that is used to mitigate multipath errors. The results show that our proposed techniques effectively improved the horizontal accuracy. In addition, the accuracy of the horizontal errors was improved by more than 50% in two different environments.