First results from the FPGA/NIOS Adaptive FIR Filter Using Linear Prediction Implemented in the AERA Radio Stations to Reduce Narrow Band RFI for Radio Detection of Cosmic Rays
The FPGA/NIOS FIR filter based on linear prediction (LP) to suppress radio frequency interference (RFI) has been installed in several radio stations in the Auger Engineering Radio Array (AERA) experiment. AERA observes coherent radio emission from extensive air showers induced by ultra-high-energy cosmic rays to make a detailed study of the development of the electromagnetic part of air showers. Radio signals provide complementary information to that obtained from Auger surface detectors, which are predominantly sensitive to the particle content of an air shower at the surface. The radio signals from air showers are caused by the coherent emission due to geomagnetic and charge-excess processes. These emissions can be observed in the frequency band between 10 - 100 MHz. However, this frequency range is significantly contaminated by narrow-band RFI and other human-made distortions. A FIR filter implemented in the FPGA logic segment of the front-end electronics of a radio sensor significantly improves the signal-to-noise ratio. In this paper we present first results of the efficiency of the adaptive LP FIR filter, deployed in real AERA station on pampas, with a comparison to the currently used IIR notch filter with constant coefficients. The laboratory tests confirms the stability of the filter. Using constant LP coefficients the suppression efficiency remains the same for hours, which corresponds to more than $\bf 10^{12}$ clock cycles. We compared in real conditions several variants of the LP FIR filter with various lengths and various coefficients widths (due to fixed-point representations in the FPGA logic) with the aim to minimize the power consumption for the radio station while keeping sufficient accuracy for noise reduction.