|Abstract:||The addition of features to authenticate satellite-based augmentation system (SBAS) signals has been under consideration since at least 1994. The considerable amount of the research conducted in this area has been focused on data authentication, i.e., adding digital signatures or other data elements to provide SBAS users assurance that the broadcast messages were generated by a trusted service provider. Authentication features have also been considered for other civilian Global Navigation Satellite System (GNSS) signals in prior research. This prior work has focused on both data authentication and signal authentication. Whereas data authentication methods primarily aim to protect GNSS signal message content from spoofing threats, signal authentication methods aim to additionally protect the ranging information. This paper proposes and assesses signal authentication methods for SBAS L1 and L5 signals. The proposed method involves puncturing the SBAS pseudorandom noise (PRN) codes with watermarks in an adaptation of the Chips Message Robust Authentication (Chimera) scheme that will be tested for the GPS L1C signal on Navigation Technology Satellite – 3 (NTS-3). An exemplary watermark detection method is defined for the purpose of evaluating performance metrics for the proposed watermark scheme. Evaluated performance metrics include probability of watermark detection as a function of received C/N0 and desired false alarm probability and correlation loss for non-participants. Implications for receiver capabilities for users that wish to process this signal are explored.|
Proceedings of the 35th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2022)
September 19 - 23, 2022
Hyatt Regency Denver
|Pages:||3369 - 3377|
|Cite this article:||
O’Hanlon, Brady, Rushanan, Joseph J., Hegarty, Christopher, Anderson, Jason, Walter, Todd, Lo, Sherman, "SBAS Signal Authentication," Proceedings of the 35th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2022), Denver, Colorado, September 2022, pp. 3369-3377.
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