During the past few years the Trend Filtering Algorithm (TFA) has become an important utility in filtering out time-dependent systematic effects in photometric databases for extrasolar planetary transit search. Here we present the extension of the method to multiperiodic signals and show the high efficiency of the signal detection over the direct frequency analysis on the original database derived by todays standard methods (e.g., aperture photometry). We also consider the (iterative) signal reconstruction that involves the proper extraction of the systematics. The method is demonstrated on the database of fields observed by the HATNet project. A preliminary variability statistics suggests incidence rates between 4 and 10% with many (sub)mmag amplitude variables.
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