Using Lagrange multiplier method and matrix differential operation, three information fusion estimation criterions are presented in the linear minimum variance sense, where the fusion estimators are respectively weighted by matrices, weighted by scalar and weighted by scalar on components. The correlation among estimation errors is considered. The results of existing literatures are extended and developed. Their precision and computational burdens are compared. They can be applied into optimal information fusion estimation for the states or signals.