In this paper, we address the identification problem of a continuous-time stochastic system. We propose approximating the system using orthonormal continuous basis functions, particularly the Kautz basis functions. We assume that only discrete-time measurements are available. The estimation problem is approached through a frequency domain identification algorithm based on the Whittle likelihood function. We illustrate the benefits of our proposal with numerical simulations.