Improved Measurement Noise Covariance Estimation for N-channel Feedback Cancellation Based on the Frequency Domain Adaptive Kalman Filter

Acoustic feedback cancellation has gained a major and steady role in the research fields of signal processing over the past decades, since it is inevitable for numerous applications such as hearing aids or in-car communication systems. In this paper, we investigate measurement noise covariance estimation approaches for feedback cancellation based on the frequency domain adaptive Kalman filter (FDAKF). The capabilities of these estimation methods significantly affect the performance of the FDAKF. We summarize and investigate existing approaches from literature and furthermore provide two new proposals that are explicitly motivated for the use in acoustic feedback cancellation. Experimental validation in the context of an in-car communication system shows that our proposals obtain much better speech quality compared to existing approaches and additionally increase the overall feedback suppression.