|Abstract:||Our work highlights the improved robustness of Phasor Measurement Units (PMUs) against meaconing i.e., record and replay attack by incorporating new protective measures to our prior work on Direct Time Estimation (DTE). In this paper, we propose a novel GPS spoofer localization based Multi-Receiver Direct Time Estimation (MRDTE) algorithm by leveraging the geometrical diversity of multiple receivers. DTE performs non-coherent summation across the satellites to evaluate the likelihood of the clock candidates considered from a pre-generated search space. Firstly, we execute DTE based multiple peak vector correlation to detect the presence of spoofer. Thereafter, we compare the time-delayed similarity in the signal properties across the geographically distributed receivers to distinguish these spoofing signals. Lastly, we perform non-coherent summation across the satellites at individual receiver level and then incorporate a Joint Filter module. This module includes a Particle Filter to estimate the spoofer location and a Kalman Filter to collectively process the maximum likely clock parameters obtained from individual receivers to estimate the precise UTC time. We validate our algorithm under a complex case of meaconing attack generated by recording the GPS signals in the same place as our multi-receiver setup and later replaying them from a different location with higher power. Our experimental results demonstrate precise localization of the spoofer while simultaneously computing the GPS time to within the accuracy specified by the power community (IEEE C37.118).|
Proceedings of the 30th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2017)
September 25 - 29, 2017
Oregon Convention Center
|Pages:||2780 - 2784|
|Cite this article:||
Bhamidipati, Sriramya, Gao, Grace Xingxin, "GPS Spoofer Localization for PMUs using Multi-Receiver Direct Time Estimation," Proceedings of the 30th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2017), Portland, Oregon, September 2017, pp. 2780-2784.
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