GNSS Anti-Spoofing for a Multi-Element Antenna Array

New optimization-based methods are developed to use measured Direction-of-Arrival (DoA) information in order classify received GNSS signals into authentic and spoofed sets. These methods are designed for a resilient GNSS system that is being developed to mitigate GNSS spoofing and jamming by using signals from a small antenna array which consists of a set of patch antennas arranged in a "bug-eye" shape. The spoofing classification method of the present paper operates on the DoA outputs of the various signals' trackers. The new method also uses the trackers' computed estimation error covariances for their DoA estimates. The contribution of this paper is a multi-hypothesis test that considers all possible hypotheses about the authentic and spoofed sets of tracked signals. A combinatorial analysis is performed in order to generate all possible authentic-set/spoofed-set classifications for the given set of tracked signals and determine the correct authentic set among the different combinations. Results from Monte Carlo runs show that using DoA methods is suitable for determining the correct combinations, assuming there is large direction separation between the authentic GNSS signals and the spoofed signals. However, when using DoA and pseudorange techniques one can determine the correct combination regardless of the direction separations. Results also indicated that the assumptions made during the paper can be relaxed in order to successfully handle other scenarios, such as multiple directional spoofers.