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Conference papers
Signal Quality Monitoring Algorithm Applied to Galileo Signals for Large Evil Waveform Threat Space
Abstract : After the observed Evil Wave Form (EWF) event in 1993, an ICAO Threat Model (TM) and Threat Space (TS) are proposed for GPS L1 C/A signal to characterize those distortions [1]. Then, a Signal Quality Monitoring (SQM) algorithm is designed to protect civil aviation users from the potential risk of these signal anomalies. Under the development of new ICAO standards for Galileo, the EWF for Galileo signals have to be characterized in order to design suitable SQM algorithm to protect aviation user when using those new signals in operation. Based on the ICAO TM and the TS adapted to Galileo signals, a SQM design needs to be defined for Galileo E1 and E5 signals in Dual Frequency Multi-Constellation (DFMC) systems. This paper focuses on the SQM design and compliance test when considering a very large EWF TS including the Galileo TS. The hazardous EWF cases that need to be detected by the SQM are those characterized by a differential bias larger than the Maximum tolerable Error (MERR) within the tested TS. The EWF differential bias is defined as the worst bias observed when the anomaly occurs on the satellite after (called rising scenario) or before (called risen scenario) it is being monitored by the SBAS reference stations. The required missed detection and false alarm probabilities for the tested TS are evaluated based on the called time-varying MERR methodology [2] and SBAS parameters. The paper proposes a SQM and code pseudorange jump monitor (CCI) that is compliant with the SBAS integrity and continuity requirements considering the TS for Galileo signals
Cited literature [10 references]
https://hal-enac.archives-ouvertes.fr/hal-02549094
Contributor : Laurence Porte <>
Submitted on : Wednesday, April 29, 2020 - 11:07:14 AM
Last modification on : Tuesday, November 3, 2020 - 8:56:54 PM
Contributor : Laurence Porte <>
Submitted on : Wednesday, April 29, 2020 - 11:07:14 AM
Last modification on : Tuesday, November 3, 2020 - 8:56:54 PM
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EWF_TS_detectability_v1.3 .pdf
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