Kalman filter based stereo system identification with auto- and cross-decorrelation

In stereo or multi-channel system identification, the most critical problems regarding online identification, e.g., for acoustic echo control, are the correlation properties of the excitation signals of the different audio channels. In this paper the impact of both the auto- and cross-correlation properties is considered and investigated. A new system combining appropriate decorrelation techniques with a Kalman filter driven adaptation algorithm in the frequency domain is presented. For the auto-decorrelation a new structure is proposed where the signals in the adaptation paths are decorrelated via linear prediction without affecting the acoustic signals. A small non-linearity is added into each channel for the reduction of the cross-correlation between channels. The performance evaluation clearly shows the influence of the different countermeasures and the effectiveness of the combined approach.