Implementation of Audio Recognition System for Unmanned Aerial Vehicles

Abstract

It is important to establish protocols for dealing with suspicious Unmanned Aerial Vehicles (UAVs). To do this, it is necessary to develop efficient UAV recognition systems. This paper describes the process of planning and implementing a drone recognition system that focuses on the audio signals generated by UAVs. To do this, a small UAV audio data set was created, using Mel Frequency Cepstral Coefficients as the audio feature analyzed by both a Support Vector Machine model (SVM) and a Convolutional Neural Network (CNN) to create a system able of recognizing the audio generated by UAVs. The resulting system was evaluated and compared, and based on the results, the SVM models was chosen to implement the audio recognition system. Further advantages and disadvantages of UAV audio signal recognition systems, as well as recommendations for their implementation were noticed during this research.