In this paper, we present a processing technique to determine the statistical distribution of additive measurement noise in real-world acquisitions, with specific reference to Phasor Measurement Unit (PMU) applications in Active Distribution Networks (ADNs). The proposed approach identifies the power signal fundamental component, as well as harmonic and interharmonic interferences, and models the measurement noise as a Gaussian random variable. First, we describe the algorithm main stages and the criteria for the most suitable parameter setting. Then, we carry out a numerical validation inspired by IEEE Std. C37.118.1 test conditions. Finally, we validate the proposed approach on real-world measurements acquired by a PMU in the distribution network of EPFL campus.