Study of the state of the art techniques for rotor noise suppression from microphone mounted on UAV
An Unmanned Aerial Vehicle when mounted with a beamformer can serve as a security surveillance platform for agencies or organization. Beamformer is a spatial filter used to collect acoustic signals from a specific direction which allow it to pick up signal from the ground. However the above Unmanned...
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Format: | Final Year Project |
Language: | English |
Published: |
2017
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Subjects: | |
Online Access: | http://hdl.handle.net/10356/71628 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | An Unmanned Aerial Vehicle when mounted with a beamformer can serve as a security surveillance platform for agencies or organization. Beamformer is a spatial filter used to collect acoustic signals from a specific direction which allow it to pick up signal from the ground. However the above Unmanned Aerial Vehicle application poses certain problem. The noise as well as the speech signal will be picked up by the microphone which is not desired.
In this report, the author will look at the possible techniques that aids in the removal of noise from the speech signal. One of the technique involved will be a resampling algorithm that resample a varying time signal to its fundamental frequency. The difference between the resampled and non resampled signal lies in the frequency component of their respective signal. By taking the spectrogram of the resampled signal, one frequency component will be showed in the plot. A filter can eventually be used to easily filter away the undesired frequency component. However in the context of a varying time signal, the multiple frequency component existing in the signal will make
filtering task a challenge. Another technique called Order Analysis will also be further explored.
The report will be divided into five chapters with chapter one stating the purpose and objective of the project while chapter two elaborating the working principle of Order Analysis. Next the project requirement outcome pertaining to the algorithm will be discussed in greater details in chapter three. Finally, the author will end this report with the presentation of the final developed algorithm as well as recommending the future areas of development for the project. |
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