Optimal Input Design for Autoregressive Model Discrimination with Constrained Output Variance

The optimal input design problem is considered for discriminating two autoregressive models when the output variance is constrained. It is shown that a Ds-optimal input design can be achieved with an input comprising a finite number of sinusoidals with amplitudes and frequencies determined by solving a system of nonlinear equations. Digital simulation studies illustrate the usefulness of the proposed Ds-optimal input for autoregressive model discrimination.