Use of Acoustic Signature for Detection, Recognition and Direction Finding of Small Unmanned Aerial Vehicles

• Published in: 2020 IEEE 15th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET) pp. 1 - 4
• Main Authors: Kartashov, Vladimir, Oleynikov, Vladimir, Koryttsev, Igor, Sheiko, Sergiy, Zubkov, Oleh, Babkin, Stanislav, Selieznov, Ivan
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-02-2020
• Subjects: acoustic emission; DJI Phantom; Mel-Frequency cepstral coefficients method; quadcopter; UAV
• DOI: 10.1109/TCSET49122.2020.235458

Unmanned aerial vehicles can fly in an autonomic flight mode without any active radio control or passive radio navigation and they are almost invisible for radars. Only engines and propellers acoustic emission (AE) may give lots of information for their detection, recognition and location. This paper discusses the experimental results of testing the classical detection and direction finding methods by Bartlett, Capeon and cross-correlation function method with the use of microphone array. Experiments include physical investigations of the UAV acoustic emission presented with two signal models - harmonic signal and broadband signal and for two conditions, namely, indoor and in the open area. Detection and recognition the UAV on a noisy background by spectral signs give the same quality as the Mel-Frequency cepstral coefficients method, but don't need to make acoustic portraits. The cross-correlation function method gives the best results in direction finding of the UAV.