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GNSS Multipath Detection Using Continuous Time-Series C/N0.
Nobuaki Kubo1, Kaito Kobayashi1, Rei Furukawa1
1Department of Maritime Systems Engineering, Tokyo University of Marine Science and Technology, Tokyo 135-8533, Japan.
Sensors (Basel, Switzerland)
|July 26, 2020
Summary
This study introduces a new Global Navigation Satellite System (GNSS) method using C/N0 signal data to detect and mitigate non-line-of-sight (NLOS) errors, significantly improving positioning accuracy in urban environments.
Area of Science:
- Geomatics Engineering
- Satellite Navigation Systems
- Signal Processing
Background:
- Multipath errors, particularly from non-line-of-sight (NLOS) signals, pose a significant challenge in Global Navigation Satellite System (GNSS) accuracy.
- Correctly identifying line-of-sight (LOS) satellites is difficult in dense urban areas, even with advanced GNSS receivers.
Purpose of the Study:
- To develop and validate a novel method for detecting NLOS signals using GNSS C/N0 data.
- To mitigate multipath errors and enhance the performance of differential GNSS, especially in challenging urban environments.
Main Methods:
- Utilizing the Carrier-to-Noise density ratio (C/N0) of GNSS signals to identify NLOS signals.
- Implementing a time-series analysis of C/N0, where a satellite is excluded from positioning if its C/N0 falls below a threshold for a sustained period.
- Conducting static tests in urban areas with high-rise buildings in Tokyo.
Main Results:
- The proposed method effectively mitigates multipath errors by reliably removing NLOS signals.
- The C/N0 time-series analysis proved more robust than simple thresholding in preventing positioning errors caused by fluctuating signals.
- Substantial improvements in differential GNSS accuracy were observed.
Conclusions:
- The developed C/N0-based method offers a significant advancement in mitigating multipath errors in GNSS.
- This approach enhances the reliability and performance of real-time kinematic (RTK) GNSS in complex urban settings.
- The study demonstrates the effectiveness of analyzing C/N0 time-series for robust NLOS signal detection.
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