A transfer function estimation procedure that relies on the time-frequency analysis of input and output signals is described. This method was developed in an attempt to better identify the aeroelastic behavior of NASA Dryden's F-18 systems research aircraft and to predict its flutter boundaries using in-flight experimental data. Numerical experiments on field data show that exploiting the time-frequency characteristics of the excitation inputs can bring enhanced accuracy and confidence when identifying multi-input/multi-output transfer functions. In particular, the proposed approach complements many well-established black-box identification procedures by providing an independent way to obtain transfer function estimates. A computational tool implementing this approach is now being evaluated for practical use at NASA Dryden Flight Research Center.