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This paper proposes a GPS spoofing detection method based on multi-sensor data fusion for the possible GPS spoofing of UAVs in the actual process. The method compares the position information corrected by multi-sensor inertial navigation system and Elman neural network with the position information of GPS output, so as to determine whether the UAV GPS is deceived. The method has two innovations. The first one is to use Elman neural network, which is helpful to improve the accuracy of the output position information of the inertial navigation system without increasing the cost of sensors. The second innovation is to use the extended Kalman filters with delays for solving the problem of multi-sensor data out of sync. Experiments show that the proposed method can effectively detect GPS spoofing, thus ensuring the safe flight of drones.