| Paper ID | B-1-2.4 |
| Paper Title |
ESTIMATING DRONE MOTOR RELATED ACOUSTIC TRANSFER FUNCTION: A PRELIMINARY INVESTIGATION |
| Authors |
Wageesha Manamperi, Thushara Abhayapala, Jihui Zhang, Prasanga Samarasinghe, Australian National University, Australia |
| Session |
B-1-2: Adaptive and Intelligent Signal Processing |
| Time | Tuesday, 08 December, 15:30 - 17:00 |
| Presentation Time: | Tuesday, 08 December, 16:15 - 16:30 Check your Time Zone |
|
All times are in New Zealand Time (UTC +13) |
| Topic |
Signal and Information Processing Theory and Methods (SIPTM): |
| Abstract |
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 behaviour using a higher order polynomial function. A detailed error analysis is presented to validate the model. |