This paper considers the problem of robust, set membership identification of parametric LTI plants, using frequency domain data. We consider the case of noisy data, and provide tractable, LMI-based conditions for computing inner and outer approximations to the set of parameters so that the resulting plant is consistent with a given a priori information and interpolate the experimental data. The results presented here are useful for model (in) validation, robust control synthesis and fault diagnosis.