A state-space partitioned-block adaptive filter for echo cancellation using inter-band correlations in the Kalman gain computation

A partitioned-block-based architecture for a model-based acoustic echo canceller in the frequency domain was recently presented. Partitioned-block-based frequency domain adaptive filters provide a lower algorithmic delay compared to the non-partitioned formulations, which is achieved by partitioning the acoustic echo path and hence shortening the time-frequency transforms. Under these circumstances, avoiding the linearisation of the involved circular convolutions can significantly impair the performance. This paper extends the already proposed diagonalization of the Kalman gain matrix by taking into account the neglected inter-band correlations to improve the performance of the acoustic echo canceller. This comes at the cost of a moderate increase in the algorithmic complexity.