Reduced-order estimators for linear discrete-time systems

In many applications, computer requirements and sensitivity to modeling errors can be reduced by using an estimator of much lower order than the system. The techniques discussed here produce reduced-order estimators which minimize the variance of the estimation error. These minimum-variance reduced-order estimators provide systematic guidelines for designing reduced-order estimators and quantitative criteria for evaluating the performance of heuristically designed estimators.