An Effective RF-Based Solution for Drone Detection and Recognition Amid Noise, Bluetooth, and Wi-Fi Interference

Recent advancements in drone technology have raised significant security concerns, making the classification of drone types for early warning systems increasingly vital. This paper presents an effective solution that combines frequency domain signal transformations with deep learning models to improve drone detection accuracy. Our approach consists of four main stages: i) RF Signal Acquisition; ii) Energy Detection and Wavelet Transformation; iii) Relevant Signal Identification and Noise Elimination; iv) Area Enhancement and Drone ClassificationWe evaluated our model using real-world and publicly available datasets. Results indicate that our method demonstrates strong noise tolerance and optimal performance across both testing sets.