  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.
