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During the past few years the Trend Filtering Algorithm (TFA) has become animportant utility in filtering out time-dependent systematic effects inphotometric databases for extrasolar planetary transit search. Here we presentthe extension of the method to multiperiodic signals and show the highefficiency of the signal detection over the direct frequency analysis on theoriginal database derived by today's standard methods (e.g., aperturephotometry). We also consider the (iterative) signal reconstruction thatinvolves the proper extraction of the systematics. The method is demonstratedon the database of fields observed by the HATNet project. A preliminaryvariability statistics suggests incidence rates between 4 and 10% with many(sub)mmag amplitude variables.

Application of the Trend Filtering Algorithm in the search for multiperiodic signals