Bounds on estimation errors of discrete-time filters under modeling uncertainty

The performance of Kalman-type linear discrete-time filters in the presence of modeling errors is considered, and bounds are obtained for the performance index, the mean-squared error of estimates for suboptimal filters. The computation of these bounds requires information on only the model matrices and the range of errors for these matrices. Consequently, a designer can easily evaluate the performance of a suboptimal filter when only the range of errors in the elements of the model matrices is available.