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The paper presents an intelligent method for detecting UAV spoofing. A distinctive feature of the method is the use of subtrajectory calculation technology based on visual odometry subtrajectories and GPS positions in a sliding window, taking into account the intelligent estimation of the optical flow and the formation of UAV “Ego-movement” descriptors. In the course of the study, an analysis and comparative studies of a wide range of UAV spoofing methods were carried out, the most frequently recommended and practically used methods were identified. The conclusion is made about the relevance of the problems of GPS spoofing. The analysis of methods of protection against UAV GPS spoofing has been carried out. Promising directions for intelligent detection of UAV spoofing using methods and means of visual odometry are identified. In the course of studying methods for fixing input data, an approach was proposed for estimating the optical flow using a sliding window. At the same time, the need for intelligent processing of input data is argued. The estimation of the optical flow and the formation of descriptors was carried out using recurrent convolutional neural networks. As a result, a block diagram of the UAV spoofing detection method was developed. This allowed us to study the developed method. The results of the experiment for two spoofing scenarios showed the efficiency of estimating the positions of at least two of the three indicators under the conditions of using sliding windows of size 15 or more, with a time delay of half the window size.
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