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Session D4: Anti-Jam and Anti-Spoofing Technologies 2

Identification of Authentic and Simulated GNSS Signals with Carrier Phase Measurements in a multi-GNSS SDR receiver
Zhen Zhu, East Carolina University; Sanjeev Gunawardena, Air Force Institute of Technology; Eric Vinande, Jason Pontious, Air Force Research Lab
Location: Room 1-3
Date/Time: Monday, Jun. 1, 4:05 p.m.

In our previous work [1], we discussed how to identify live GNSS signals when they are mixed with an unknown group of self-consistent simulated signals, using measurements recorded by PyChips [2], a software defined radio receiver. PyChips measured code phase, carrier phase and navigation data from all the available channels, including live and simulated channels. When inauthentic signals are purposely disguised to behave like authentic ones, they could be consistent among each other and be consistent between measurements and navigation data. It would be more difficult to identify them in the measurement domain by checking signals or satellites individually. However, authentic GNSS measurements will always agree with the actual motion and clock characteristics of the receiver and the satellites. In spite of noise and errors, there is an inherent consistency that lies within all authentic GNSS measurements. On the other hand, it is much less likely for inauthentic signals to maintain such consistency at all the levels or over time.
We also demonstrated in [3] that the consistency among all available GNSS constellations and signals can be checked with time-differenced carrier phase (TDCP) measurements. Normally, an integrated multi-constellation positioning solution would always require information on the inter-system timing bias. However, this bias can be cancelled via time differencing. Therefore, all available GNSS satellites can be combined into a single TDCP measurement model. The number of authentic TDCP measurements in a multi-constellation, multi-frequency receiver is typically in the range of 20 to 40, which results in great redundancy in the measurement set. A Random sample consensus (RANSAC) algorithm was also introduced in [3] to detect a group of TDCP measurements that are consistent with each other.
Since the live signals were consistent with satellite orbital/clock models and the receiver clock model, and were consistent among each other, they can be differentiated from the simulated ones. It has been shown in [1] that simulated signals and their solutions can be clearly identified in a carrier phase solution by the RANSAC algorithm. However, since the simulated signals were not from a controlled source, it was not feasible to validate whether the simulated solution estimated in this process was accurate.
In this work, GNSS signals from controlled simulators will be used instead. Carrier phase and navigation data will be extracted by using PyChips, from which RANSAC will be used to identify simulated signals. The displacement solution calculated using the identified simulated signals will be compared against the simulator truth.
More interestingly, PyChips is able to simultaneously track all available GNSS channels. Therefore, if the live GNSS signals are mixed with multiple simulators, PyChips will still provide all the required measurements. We will also discuss a framework in which multiple simulators can be individually identified using TDCP.
[1] Zhu, Zhen, Gunawardena, Sanjeev, "Identification of Authentic GNSS Signals in Time-Differenced Carrier Phase Measurements with a Software Defined Radio," Proceedings of the 35th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2022), Denver, Colorado, September 2022, pp. 3570-3579.
[2] Gunawardena, S. (2021) "A High Performance Easily Configurable Satnav SDR for Advanced Algorithm Development and Rapid Capability Deployment," Proceedings of the 2021 International Technical Meeting of The Institute of Navigation, January 2021, pp. 539-554.
[3] Zhu, Z., Vinande, E., Pontious, J. et al. (2022). A robust multi-constellation time-differenced carrier phase solution. GPS Solut 26, 8.
This document has been approved for public release, distribution unlimited. Case Number AFRL-2024-0407

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