Deep Learning Based Malicious Drone Detection Using Acoustic and Image Data

2022 Sixth IEEE International Conference on Robotic Computing (IRC)(2022)

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摘要
Drones have been studied in a variety of industries. Drone detection is one of the most important task. The goal of this paper is to detect the target drone using the microphone and a camera of the detecting drone by training deep learning models. For evaluation, three methods are used: visual-based, audio-based, and the decision fusion of both features. Image and audio data were collected from the detecting drone, by flying two drones in the sky at a fixed distance of 20m. CNN (Convolutional Neural Network) was used for audio, and YOLOv5 was used for computer vision. From the result, the decision fusion of audio and vision-based features showed the highest accuracy among the three evaluation methods.
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关键词
drone detection,audio classification,computer vision,counter unmanned aerial systems,deep learning
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