Estimating Drone Motor Related Acoustic Transfer Function: A Preliminary Investigation

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Manamperi, Wageesha
Abhayapala, Thushara
Zhang, Jihui (Aimee)
Samarasinghe, Prasanga

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IEEE

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The potential of drone based services is enormous with applications ranging from consumer product delivery to health services. When meeting this demand, one of the major challenges we face is the noise produced by drones, which not only contributes to listener discomfort, but also hinders the device's ability to effectively communicate via audio. Thus, there exists a pressing need for understanding the characteristics of drone related noise, which can then be suppressed using suitable methods. This paper presents a preliminary study on modeling the relationship between input motor current and acoustic noise produced by a drone. An experimental study is conducted indoors for a drone under hovering manoeuvre with a single active motor and propeller. The drone noise was measured by a single on-board microphone. We identify multiple tones or harmonics in the drone noise spectrum that vary proportionally to the motor current. Based on this observation, we define a transfer function between the input current and output noise, and model its harmonic behavior using a higher order polynomial function. A detailed error analysis is presented to validate the model.

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2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)

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2099-12-31