Abstract
Knowledge of the signal-in-space (SIS) anomaly probability is important for the integrity monitoring of satellite navigation. An efficient SIS anomaly detection method is indispensable for characterizing the probability of SIS anomalies with sufficient confidence. The traditional GPS anomaly detection method based on the zero-mean Gaussian distribution assumption of the instantaneous signal-in-space user range error (IURE) is not suitable for the emerging BeiDou navigation satellite system (BDS) because of the nonzero-mean, asymmetric distribution of the BDS IURE. By deliberately extracting the time series trend terms of the satellite orbit and clock errors, an SIS anomaly detection method with the worst user location protection principle is proposed based on 6 years of BDS data from March 2013 to March 2019. The detection results have shown that the probability of single-satellite SIS anomalies is at the 10−3 level and the probability of multiple-satellite SIS concurrent anomalies is at the 10−4 level. Meanwhile, the operational service performance provided by the BDS gradually improves over time.
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Data availability
The broadcast ephemeris that supports the findings of this study is openly available at ftp://ftp.cddis.eosdis.nasa.gov/gnss/data/campaign/mgex/daily/rinex3/ (last accessed on February 04, 2020). The precise ephemeris that supports the findings of this study is openly available at ftp://igs.ign.fr/pub/igs/products/mgex/ (last accessed on February 04, 2020). Other data generated or analyzed during this study are presented in this article.
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Acknowledgements
The authors gratefully acknowledge IGS organization and Wuhan University for providing the broadcast ephemeris and precise ephemeris used. This research was jointly funded by the National Natural Science Foundation of China (Nos. 61773132, 61633008, 61803115, 62003109), the National Key Research and Development Program (No. 2017YFE0131400), the 145 High-tech Ship Innovation Project sponsored by Chinese Ministry of Industry and Information Technology, the Heilongjiang Province Research Science Fund for Excellent Young Scholars (No. YQ2020F009), the Heilongjiang Province Research Science Fund for Distinguished Young Scholars (No. JC2018019) and the Fundamental Research Funds for Central Universities (Nos. 3072019CF0401, 3072020CFJ0402, 3072020CFT0403).
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Zhao, Y., Cheng, C., Li, L. et al. BDS signal-in-space anomaly probability analysis over the last 6 years. GPS Solut 25, 49 (2021). https://doi.org/10.1007/s10291-021-01097-z
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DOI: https://doi.org/10.1007/s10291-021-01097-z