This is a new spectral analysis method for the identification of periodic signals in geophysical time series. We evaluate the power spectral density with the adaptive multitaper method, a sophisticated non-parametric spectral analysis technique suitable for time series characterized by colored power spectral density. Our method provides a maximum likelihood estimation of the power spectral density background according to four different models. It includes the option for the models to be fitted on four smoothed versions of the power spectral density when there is a need to reduce the influence of power enhancements due to periodic signals. We use a statistical criterion to select the best background representation among the different smoothing+model pairs. Then, we define the confidence thresholds to identify the power spectral density enhancements related to the occurrence of periodic fluctuations. We combine the results with those obtained with the multitaper harmonic F test, an additional complex-valued regression analysis from which it is possible to estimate the amplitude and phase of the signals. A complete description of the procedure is available at: Di Matteo, S., Viall, N. M., & Kepko, L. (2021). Power spectral density background estimate and signal detection via the multitaper method. Journal of Geophysical Research: Space Physics, 126, e2020JA028748. https://doi.org/10.1029/2020JA028748