LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

GPS Multireceiver Joint Direct Time Estimation and Spoofer Localization

Photo from wikipedia

We propose a novel algorithm for the joint estimation of spoofer location (LS) and GPS time using multireceiver direct time estimation (MRDTE). To achieve this, we utilize the geometry and known positions… Click to show full abstract

We propose a novel algorithm for the joint estimation of spoofer location (LS) and GPS time using multireceiver direct time estimation (MRDTE). To achieve this, we utilize the geometry and known positions of multiple static GPS receivers distributed within the power substation. The direct time estimation computes the most likely clock parameters by evaluating a range of multipeak vector correlations, each of which is constructed via different pregenerated clock candidates. Next, we compare the time-delayed similarity in the identified peaks across the receivers to detect and distinguish the spoofing signals. Later, we localize the spoofer and estimate the GPS time using our joint particle and Kalman filter. Furthermore, we characterize the probability of spoofing detection and false alarm using Neyman Pearson decision rule. Later, we formulate the theoretical Cramér Rao lower bound for estimating the localization accuracy of the spoofer. We validate the robustness of our LS-MRDTE by subjecting the authentic open-sky GPS signals to various simulated spoofing attack scenarios. Our experimental results demonstrate precise localization of the spoofer while simultaneously estimating the GPS time to within the accuracy specified by the power community (IEEE C37.118 standard for synchrophasors).

Keywords: time; spoofer; direct time; time estimation; estimation; gps

Journal Title: IEEE Transactions on Aerospace and Electronic Systems
Year Published: 2019

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.