The article presents the FPGA implementation of 256- and 768-stage Least Mean Squares filters with rectangular, Hamming and Kaiser windows to suppress at least ten narrowbands RFIs. The analysis ...shows extremely high-efficiency Radio Frequency Interference (RFI) elimination. For a proof of concept study, we used 9-bit real cosmic ray data from the Auger Engineering Radio Array (AERA) as patterns and mixed with 14-bit multiple narrow-band RFIs. They were hidden deep within RFI’s background. After the cleaning process, the patterns were brought out and have shown practically without contamination.
We are presenting a new approach to a filtering of radio frequency interference (RFI) in the Auger Engineering Radio Array (AERA), which studies the electromagnetic part of the extensive air showers. ...Radio stations can observe radio signals caused by coherent emissions due to geomagnetic radiation and charge excess processes. AERA observes the frequency band from 30 to 80 MHz. This range is highly contaminated by human-made RFI. In order to improve the signal to noise ratio RFI filters are used in AERA to suppress this contamination. The filter has already been tested with real AERA radio stations in the Argentinean Pampas with very successful results. The linear equations were solved either in the virtual soft-core NIOS® processor (implemented in the FPGA chip as a net of logic elements) or in the external Voipac PXA270M ARM processor. The NIOS® processor is relatively slow (50 MHz internal clock), and the calculations performed in an external processor consume a significant amount of time for data exchange between the FPGA and the processor. Tests showed very good efficiency of the RFI suppression for stationary (long-term) contaminations. However, we observed short-time contaminations, which could not be suppressed either by the IIR-notch filter or by the FIR filter based on the linear predictions. For the LP FIR filter, the refresh time of the filter coefficients was too long and the filter did not keep up with the changes in the contamination structure, mainly due to a long calculation time in a slow processors. We propose to use the Cyclone® V SE chip with an embedded micro-controller operating with a 925 MHz internal clock to significantly reduce the refreshment time of the FIR coefficients. First results in the laboratory are very promising.
The production of radio waves from extensive air showers (EASs), initiated by ultra-high-energy cosmic rays, has been attributed to geomagnetic emission and charge excess processes. These days, the ...radio detection technique is used in many experiments aimed at studying EAS. One of them is the Auger Engineering Radio Array (AERA), located within the Pierre Auger Observatory. The frequency band observed by AERA radio stations is 30-80 MHz. The investigated frequency range is often very contaminated by human-made and narrowband radio-frequency interference (RFI). Suppression of these contaminations is crucial to lowering the rate of spurious triggers. An adaptive filter based on the least mean squares (LMS) algorithm can be an alternative one for currently used infinite impulse response (IIR)-notch nonadaptive filters. Measurements show that the LMS filter is very efficient in suppressing RFI and only slightly distorts radio signals. This article presents the 32-stage filters based on a transposed finite impulse response (FIR) filter implemented into cost-effective CycloneIV and CycloneV Altera field-programmable gate arrays (FPGAs) with a sufficient safety margin of the timing performance for the global clock above 200 MHz to obey the Nyquist requirement.
Extensive Air Showers (EAS), initiated by Ultra-High-Energy Cosmic Rays (UHECRs), generate geo-synchrotron and geo-magnetic radiations and they are, also, the source of excess charge processes. In ...the frequency range of 10 to 100 MHz, coherent radiation is formed. Many experiments use the radio detection technique for studying EAS features. The Auger Engineering Radio Array (AERA), part of the Pierre Auger Observatory, uses hundreds of radio antennas working in the frequency range of 30 to 80 MHz to support the investigation of UHECRs together with the standard surface and fluorescence detectors. The AERA radio frequency range is significantly contaminated by the human-made and usually narrow-band Radio Frequency Interference (RFI), e.g., shortwave radio transmitters. The presence of RFIs in the detected signals increases the ratio of spurious triggers; in consequence, empty data inflate the databases. This study proposes replacing the currently used IIR-notch nonadaptive filter by the delayed version of the wellknown Least Mean Squares (LMS) algorithm, which offers crucial advantage adjustment. The current study implemented 32/64-stage Delay Least Mean Squares (DLMS) filters on cost-effective Cyclone® IV and Cyclone® V as non-canonical Finite Input Response (FIR) with a sufficient safety margin for a global clock being at least 20% higher than 200 MHz, which equals the ADC sampling frequency.
Radio emission from the extensive air showers (EASs), initiated by ultrahigh-energy cosmic rays, was theoretically suggested over 50 years ago. However, due to technical limitations, successful ...collection of sufficient statistics can take several years. Nowadays, this detection technique is used in many experiments consisting in studying EAS. One of them is the Auger Engineering Radio Array (AERA), located within the Pierre Auger Observatory. AERA focuses on the radio emission, generated by the electromagnetic part of the shower, mainly in geomagnetic and charge excess processes. The frequency band observed by AERA radio stations is 30-80 MHz. Thus, the frequency range is contaminated by human-made and narrow-band radio frequency interferences (RFIs). Suppression of contaminations is very important to lower the rate of spurious triggers. There are two kinds of digital filters used in AERA radio stations to suppress these contaminations: the fast Fourier transform median filter and four narrow-band IIR-notch filters. Both filters have worked successfully in the field for many years. An adaptive filter based on a least mean squares (LMS) algorithm is a relatively simple finite impulse response (FIR) filter, which can be an alternative for currently used filters. Simulations in MATLAB are very promising and show that the LMS filter can be very efficient in suppressing RFI and only slightly distorts radio signals. The LMS algorithm was implemented into a Cyclone V field programmable gate array for testing the stability, RFI suppression efficiency, and adaptation time to new conditions. First results show that the FIR filter based on the LMS algorithm can be successfully implemented and used in real AERA radio stations.
The emission of radio waves from air showers has been attributed to the so-called geomagnetic emission process. At frequencies around 50 MHz this process leads to coherent radiation, which can be ...observed with rather simple setups. Thus, the radio detection technique is used in many experiments consisting in studying extensive air showers. One of them is the Auger Engineering Radio Array (AERA), located within the Pierre Auger Observatory. The frequency band observed by AERA radio stations is 30-80 MHz. This range is highly contaminated by human-made radio-frequency interferences (RFI). In order to improve the signal to noise ratio the filter has to be used to suppress these contaminations, crucial to lower the rate of spurious triggers. The presented filter derived from the Least Mean Squares (LMS) approach can be an potentially new solution instead of the currently in use IIR-notch non-adaptive filter. 32/64-stage filters based on non-canonical FIR filter implemented into cost-effective Altera FPGAs with a sufficient safety margin of the registered performance for the global clock above 200 MHz to obey the Nyquist requirement, proved a very good RFI suppression for typical radio-frequency interferences (RFI) of several mono-carriers for a wide spectrum of fixed learning factors. However, an arbitrary selection of the learning factor in a dynamically changing Argentinean pampas environment may not be optimal. The paper presents a modified algorithm with variable stepsize allowing a dynamically adjustment of the mi factor to changing and potentially new appearing RFI in real AERA environment.
PDF