Cyclostratigraphy and astronomical tuning utilize the imprint of quasi-cyclic insolation changes in geological records to establish chronologies. In this context, filtering of time series in specific frequency bands is commonly applied to extract information on astronomical forcing from geological datasets. This approach is performed on specific insolation components (precession, obliquity or eccentricity) and sometimes also their amplitudes either in depth or time domain. In this study, we design and apply a simulation technique to determine the optimal Taner filter settings to extract precession-, obliquity- and eccentricity-related interference signals from astronomically tuned geological datasets. This is done by testing a variety of filter settings on several astronomical and artificial datasets. Based on our results, we propose specific filter settings (cut-off frequencies and roll-off rates) for the best extraction of astronomical (interference) signals from tuned geological datasets. Focus here lies on datasets shorter than ca. 1 million years and interference patterns between astronomical components. A second step utilizes these filter settings for an automated alignment, where geological data on a tuned time scale are matched to a suite of astrochronologic correlation targets. This is done by aligning filter minima and maxima to astronomical targets. This approach is particularly useful for the determination of the relative contributions of astronomical parameters in a specific dataset and allows for the automatic determination of phase shifts between well expressed insolation components in datasets.