Fabian Rothmaier, Stanford University

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In this paper we present a sequential likelihood ratio test to detect a GNSS spoofing attack using information from multiple measurements. We develop an analytical solution for the test’s detection threshold that can be computed online by the receiver and that is optimal according to the Neyman-Pearson lemma. We present its application to both independent and correlated Direction of Arrival measurements. To demonstrate the procedure’s general applicability, we reproduce previously published simulations and apply it to data from flight tests and a live spoofing event.