Acoustic localization and tracking of a multi-rotor unmanned aerial vehicle using an array with few microphones

In recent years, the current technological improvements of unmanned aerial vehicles (UAV) have made drones more difficult to locate using optical or radio-based systems. However, the sound emitted by UAV motorization and the aerodynamic whistling of the UAVs can be exploited using a microphone array and an adequate real time signal processing algorithm. The proposed method takes advantage of the characteristics of the sound emitted by the UAV. The intrinsic harmonic structure of the emitted sound is exploited by a pitch detection algorithm coupled with zero-phase selective bandpass filtering to detect the fundamental of the signal and to extract its specific harmonics. Although three-dimensional position errors are less when signals are filtered within the antenna bandwidth, experimental measurements show that accurate estimates with only a few selected harmonics in the signal can be obtained with the localization process. Kalman filtering is used to smooth the estimates.