An Acoustic Identification Algorithm for UAV Based on Cross-Correlation

In order to detect the presence of unmanned aerial vehicles (UAVs) in the airspace accurately, this paper proposed an acoustic recognition algorithm for UAV by employing the cross-correlation method. Acoustic signal pre-processing involves the use of Short-time Fourier transform (STFT), empirical mode decomposition (EMD), and interpolation techniques. A feature of UAV acoustic signal in frequency domain is extracted. An acoustic signal matching template in frequency domain of UAV is designed for the cross-correlation calculation. Meanwhile, the threshold method is developed to classify whether UAV is present or not based on cross-correlation coefficient. Pure data from a silencer room and actual data from playground of Jianghan University are employed for analysis. The performance reports indicate that the identification rate of designed algorithm is higher than other methods and is more suitable for UAV identification.