Experiments that observe coherent radio emission from extensive air showersinduced by ultra-high energy cosmic rays are designed for a detailed study ofthe development of the electromagnetic part of air showers. Radio detectors canoperate with 100% up time as e.g. surface detectors based on water-Cherenkovtanks. They are being developed for ground-based experiments (e.g. the PierreAuger Observatory) as another type of air shower detector in addition to thefluorescence detectors, which operate with only ~10% of duty in dark nights.The radio signals from air showers are caused by the coherent emission due togeomagnetic radiation and charge excess processes. Currently used self-triggersin radio detectors often generate a dense stream of data, which is analyzedafterwards. Huge amounts of registered data requires a significant man-powerfor the off-line analysis. An improvement of the trigger efficiency becomes arelevant factor. In this work, Morlet wavelets with various scaling factors were used for ananalysis of real data from the Auger Engineering Radio Array and for anoptimization of the utilization of the resources in an FPGA. The waveletanalysis showed that the power of events is concentrated mostly in a limitedrange of the frequency spectrum (consistent with a range imposed by the inputanalog band-pass filter). However, we found several events with suspiciousspectral characteristics, where the signal power is spread over the fullband-width sampled by a 200 MHz digitizer with significant contribution of veryhigh and very low frequencies. These events may not origin from cosmic rayshowers but can be human-made contaminations. The engine of the waveletanalysis can be implemented into the modern powerful FPGA and can removesuspicious events on-line to reduce the trigger rate.
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