Model errors in Kalman filter and simple correction techniques

As techniques cf divergence reduction in Kalman filtering, the adaptive Jazwinski´s plant noise covariance matching is compared with the non-adaptive Schmidt´s gain matrix scaling. In the simple case studied, the two give comparable performances and both are effective. However, Jazwinski´s algorithm is more suitable than the non-adaptive Schmidt´s for the purpose of real time processing.