A Kalman filter with individual control factors for echo cancellation

In echo cancellation, the main goal is to recover the near-end signal from the error signal of the adaptive filter, which identifies the echo path. In this context, the Kalman filter represents a very appealing choice, since its basic criterion follows the minimization of the system misalignment (instead of the usual error-based cost function). In this paper, we propose a Kalman filter with individual control factors, in terms of using a different level of uncertainty for each coefficient of the filter. As compared to the basic Kalman filter (which imposes the same uncertainty for all the coefficients of the impulse response), the proposed algorithm achieves better performance, especially in terms of the steady-state misalignment.