Improved Kalman gain computation for multichannel frequency-domain adaptive filtering and application to acoustic echo cancellation

For multichannel adaptive filtering applications like acoustic echo cancellation, sophisticated, but efficient algorithms are necessary that take both auto- and cross-correlations of the excitation signals into account. Based on a recently published frequency-domain framework, we examine in this contribution the computation of the so-called frequency-domain Kalman gain, which is crucial in the multichannel case to meet the above requirements for correlated input signals. We present an extended scheme with increased computational efficiency for a higher number of input channels. Robust convergence behaviour during perturbation of the desired signal is ensured by a new dynamical regularization. Application of the new algorithm to multichannel acoustic echo cancellation with real-world signals achieves improved performance.