We consider the problem of constructing suboptimal filters (lower-order optimal filters, i.e., filters for linear vector functionals of the system state vector) for stochastic multivariable multicriteria plants. The method for constructing such filters is presented in the Luenberger canonical basis. Using a numerical example of a seventh-order system, we show that the proposed approach improves the optimality of filters compared to filters based on scalar observers.