Andreas Iliopoulos, C. Enneking, Omar García Crespillo, T. Jost, S. Thoelert, F. Antreich
{"title":"Multicorrelator signal tracking and signal quality monitoring for GNSS with extended Kalman filter","authors":"Andreas Iliopoulos, C. Enneking, Omar García Crespillo, T. Jost, S. Thoelert, F. Antreich","doi":"10.1109/AERO.2017.7943579","DOIUrl":null,"url":null,"abstract":"GNSS signals may present anomalies that degrade the positioning performance of GNSS receivers. Signal Quality Monitoring (SQM) is normally used to detect and to characterize these anomalies. This is required for the GNSS operators and integrity services to determine when a satellite should be considered as faulty and draw conclusions about the type of the fault. In this paper, we present a new SQM algorithm that tracks the GNSS signal and possible channel deformations by using a novel methodology based on the Extended Kalman Filter (EKF). The EKF is designed such that the measurement update is performed in post-correlation and using multiple correlators. After the estimation of the channel response, we add a detection step to determine if the channel deviates from the nominal signal transmission scenario (i.e., the single path propagation). Results suggests that the performance of the delay estimation with the proposed EKF structure outperforms the classical Delay-Locked-Loop (DLL) estimation, especially in the presence of distortions. Furthermore, it can reliably detect anomalous signal deformations as specified by ICAO threat model.","PeriodicalId":224475,"journal":{"name":"2017 IEEE Aerospace Conference","volume":"89 Pt B 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Aerospace Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AERO.2017.7943579","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
GNSS signals may present anomalies that degrade the positioning performance of GNSS receivers. Signal Quality Monitoring (SQM) is normally used to detect and to characterize these anomalies. This is required for the GNSS operators and integrity services to determine when a satellite should be considered as faulty and draw conclusions about the type of the fault. In this paper, we present a new SQM algorithm that tracks the GNSS signal and possible channel deformations by using a novel methodology based on the Extended Kalman Filter (EKF). The EKF is designed such that the measurement update is performed in post-correlation and using multiple correlators. After the estimation of the channel response, we add a detection step to determine if the channel deviates from the nominal signal transmission scenario (i.e., the single path propagation). Results suggests that the performance of the delay estimation with the proposed EKF structure outperforms the classical Delay-Locked-Loop (DLL) estimation, especially in the presence of distortions. Furthermore, it can reliably detect anomalous signal deformations as specified by ICAO threat model.