Widely linear general Kalman filter for stereophonic acoustic echo cancellation

• A general Kalman filter (GKF) is developed with the widely linear (WL) model for stereophonic acoustic echo cancellation (SAEC).
• The specific parameters of the WL-GKF allow a better control of the algorithm, as compared to the recursive least-squares (RLS) counterpart.
• The proposed WL-GKF achieves good performance in terms of convergence rate and tracking, outperforming the WL-RLS benchmark.

The stereophonic acoustic echo cancellation (SAEC) problem is usually modelled as a two-input/two-output system with real random variables. Recently, the SAEC scheme was recast as a single-input/single-output system with complex random variables, thanks to the widely linear (WL) model. In this paper, we motivate the use of a more general form of the Kalman filter with the WL model for SAEC. Simulation results indicate that this algorithm outperforms the recursive least-squares (RLS) algorithm, which is usually considered as the benchmark for SAEC.