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IEEE/ICACT20230149 Slide.08        [Big Slide]	Oral Presentation
	The commercial drone RF signals have no standardization for the RF protocol, which means that any manufacturer can create their own RF protocol and carry out the RF communication between the drone and the ground control station. State-of-the-art DNN-based classification can work with labelled samples, which means that it can only classify the signals it is trained with. When you present a novel or an unknown signal, the classification performance becomes completely unreliable. Here, we need a novelty detection method before the classification. Very limited literature addresses this RF novelty detection problem. In this study, we proposed a framework for novelty detection, known RF signal classification, and novelty clustering. We also show that the reconstruction-based novelty detection method outperforms the existing SoA methods.

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