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.