Decorrelation in Adaptive Feedback Cancellation for Public Address Systems

Bachelor thesis (2020)

Authors

L.C.A. Huijbregts Electrical Engineering, Mathematics and Computer Science
M.A. Jongepier Electrical Engineering, Mathematics and Computer Science

Contributors

Jorge Martinez Electrical Engineering Education - EEMCS (supervisor 1)
R.C. Hendriks Signal Processing Systems - EEMCS (supervisor 1)
J.E.J. Schmitz Electrical Engineering, Mathematics and Computer Science (supervisor 2)
S. Izadkhast Electrical Engineering Education - EEMCS (supervisor 2)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2020 L.C.A. Huijbregts, M.A. Jongepier
Adaptive Filtering Decorrelation Signal Processing Acoustic Feedback Cancellation Frequency Modulation PEAQ ODG AFC Digital signal processing
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Published Date

03-07-2020

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Public Address systems that include a setup with at least one microphone and speaker can suffer from acoustic feedback. This results in an annoying howling effect which can damage hardware and human hearing. To solve this issue, an adaptive filter that estimates the feedback path and uses this estimate to cancel the feedback can be designed. However, because the adaptive filter receives signals from both the microphone and the feedback, and because sound signals are generally correlated over time, the estimate becomes biased. To reduce this bias, the speaker signal can be decorrelated from the input. In this thesis several options to decorrelate these signals are explored, and they are evaluated based on decorrelation performance and effect on audio quality. Frequency shifting is selected as the best decorrelation method as it provides the most decorrelation while retaining audio quality. Finally it is shown that using Frequency Shifting to decorrelate the microphone and speaker signal indeed improves the estimation of the feedback path.