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Acoustic Estimation of the Direction of Arrival of an Unmanned Aerial Vehicle Based on Frequency Tracking in the Time-Frequency Plane
Acoustic Estimation of the Direction of Arrival of an Unmanned Aerial Vehicle Based on Frequency Tracking in the Time-Frequency Plane
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Acoustic Estimation of the Direction of Arrival of an Unmanned Aerial Vehicle Based on Frequency Tracking in the Time-Frequency Plane
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Acoustic Estimation of the Direction of Arrival of an Unmanned Aerial Vehicle Based on Frequency Tracking in the Time-Frequency Plane
Acoustic Estimation of the Direction of Arrival of an Unmanned Aerial Vehicle Based on Frequency Tracking in the Time-Frequency Plane

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Acoustic Estimation of the Direction of Arrival of an Unmanned Aerial Vehicle Based on Frequency Tracking in the Time-Frequency Plane
Acoustic Estimation of the Direction of Arrival of an Unmanned Aerial Vehicle Based on Frequency Tracking in the Time-Frequency Plane
Journal Article

Acoustic Estimation of the Direction of Arrival of an Unmanned Aerial Vehicle Based on Frequency Tracking in the Time-Frequency Plane

2022
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Overview
The development of unmanned aerial vehicles (UAVs) opens up a lot of opportunities but also brings some threats. Dealing with these threats is not easy and requires some good techniques. Knowing the location of the threat is essential to deal with an UAV that is displaying disturbing behavior. Many methods exist but can be very limited due to the size of UAVs or due to technological improvements over the years. However, the noise produced by the UAVs is still predominant, so it gives a good opening for the development of acoustic methods. The method presented here takes advantage of a microphone array with a processing based on time domain Delay and Sum Beamforming. In order to obtain a better signal to noise ratio, the UAV’s acoustic signature is taken into account in the processing by using a time-frequency representation of the beamformer’s output. Then, only the content related to this signature is considered to calculate the energy in one direction. This method enables to have a good robustness to noise and to localize an UAV with a poor spectral content or to separate two UAVs with different spectral contents. Simulation results and those of a real flight experiment are reported.