  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 today's 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.
