Radio Detection Of Cosmic Rays Research Articles

Multistage FPGA Least Mean Squares Filters Suppressing Multiple Narrowband Radio-Frequency Interferences in the Radio Detection of Cosmic Rays

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 10 narrow-bands RFIs. The analysis shows extremely high efficiency Radio Frequency Interference (RFI) elimination. 9-bit real cosmic ray data from the Auger Engineering Radio Array (AERA) was used 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 are practically without contamination.

Analysis of efficiency and quality of filters suppressing RFI in radio detection of cosmic rays

Radio stations of the Auger Engineering Radio Array (AERA) investigates radio signals from coherent emissions due to geomagnetic radiation and charge excess processes. The frequency band is limited to 30–80 MHz. In order to improve the signal to noise ratio, RFI filters have to be used to suppress this contamination.The paper compares several (currently in use and proposed) RFI filters. We analyzed: the non-adaptive filter (IIR notch) as well as adaptive filters: IIR notch supported by the virtual NIOS® processor, FIR based on the linear prediction supported by the virtual NIOS® processor and finally the Least Mean Square filter. The LMS filter proposed for the RFI suppression should use correct learning factor, crucial for a stability of the filter, which could be determined by eigenvalues of the auto-correlation matrix built for ADC samples.For typical AERA configuration (4 beacons with fixed frequencies) the best filter seems to be the IIR as introducing very high suppression efficiency with relatively low distortions and low energy consumption. However, when unexpected RFI appears it is worth consider a combination of fixed frequency IIR + IIR filter supported with NIOS processor identifying additional RFI source as well as FIR filters. LMS filters can be used when very fast response on new sources is needed.

Stable convergence of the algorithm computing the coefficients of the LMS filter suppressing RFI in radio detection of cosmic rays in the Auger Engineering Radio Array

Radio stations of the Auger Engineering Radio Array (AERA) investigates radio signals from coherent emissions due to geomagnetic radiation and charge excess processes. The frequency band is limited to 30–80 MHz. This range is highly contaminated by human-made RFI. In order to improve the signal to noise ratio, RFI filters have to be used to suppress this contamination.The LMS filter proposed for the RFI suppression should use correct learning factor, crucial for a stability of the filter, which could be determined by eigenvalues of the auto-correlation matrix built for ADC samples.A detailed analysis of almost one million of AERA events confirms that eigenvalues of real cosmic events taken from the AERA database fully allow their use in the LMS filters, with learning factors optimal for the most efficient RFI suppression.This type of the filter can be used in other radio cosmic ray experiments e.g. the Giant Radio Array for Neutrino Detection (GRAND).

The SKA particle array prototype: The first particle detector at the Murchison Radio-astronomy Observatory

We report on the design, deployment, and first results from a scintillation detector deployed at the Murchison Radio-astronomy Observatory (MRO). The detector is a prototype for a larger array – the Square Kilometre Array Particle Array (SKAPA) – planned to allow the radio-detection of cosmic rays with the Murchison Widefield Array and the low-frequency component of the Square Kilometre Array. The prototype design has been driven by stringent limits on radio emissions at the MRO, and to ensure survivability in a desert environment. Using data taken from Nov. 2018 to Feb. 2019, we characterize the detector response while accounting for the effects of temperature fluctuations, and calibrate the sensitivity of the prototype detector to through-going muons. This verifies the feasibility of cosmic ray detection at the MRO. We then estimate the required parameters of a planned array of eight such detectors to be used to trigger radio observations by the Murchison Widefield Array.

NuRadioReco: a reconstruction framework for radio neutrino detectors

While the radio detection of cosmic rays has advanced to a standard method in astroparticle physics, the radio detection of neutrinos is just about to start its full bloom. The successes of pilot-arrays have to be accompanied by the development of modern and flexible software tools to ensure rapid progress in reconstruction algorithms and data processing. We present NuRadioReco as such a modern Python-based data analysis tool. It includes a suitable data-structure, a database-implementation of a time-dependent detector, modern browser-based data visualization tools, and fully separated analysis modules. We describe the framework and examples, as well as new reconstruction algorithms to obtain the full three-dimensional electric field from distributed antennas which is needed for high-precision energy reconstruction of particle showers.

Radio detection of cosmic rays in [1.7–3.7] MHz: The EXTASIS experiment

Since 2003, significant efforts have been devoted to the understanding of the radio emission of extensive air showers above 20 MHz. Despite some studies led until the early nineties, the band available below 20 MHz has remained unused for 20 years. However, it has been claimed by some pioneering experiments that extensive air showers emit a strong electric field in this band and that there is evidence of a large increase of the radio pulse amplitude with decreasing frequencies. The EXTASIS experiment, located within the Nançay Radioastronomy Observatory and supported by the scintillator array and the autonomous radio stations of the CODALEMA experiment, aims to re-investigate the low-frequency band, and especially to study the so-called ”sudden death” contribution, the expected electric field radiated by the shower front when hitting ground level. In this work, we present the instrumental setup of the EXTASIS experiment composed of 7 low-frequency antennas operating in [1.7–3.7] MHz and covering approximately 1 km2. We report the observation of 18 air showers detected in coincidence in the three instruments, and estimate a detection threshold of 23 ± 4 µV from comparisons with detailed SELFAS3 simulations. We also report a strong correlation of the low-frequency signal observation with the atmospheric electric field.

Influence of a planar boundary on the electric field emitted by a particle shower

The radio detection of cosmic rays consists in the estimation of the properties of a primary cosmic ray by observing the electric field emitted by the extensive air shower (EAS) created when the primary cosmic ray enters the atmosphere. This technique is fully operative nowadays and presents a good degree of maturity. In addition, several projects intend to employ this technique for the detection of neutrinos. In order for the technique to be useful, accurate methods for computing the electric field created by a particle shower in the context of a particular experiment must exist. Although current ground-based radio experiments lie on the air-soil interface and some planned experiments on the South Pole envision antennas near the air-ice interface, most of the analytical approaches and Monte Carlo codes used for calculating the electric field either do not take into account the effect of the boundary or calculate the radiation fields only (direct, reflected and transmitted radiation fields). When the particle shower and the antenna are close to the boundary, compared to the observation wavelength, the far-field approximation breaks down, which is the case for the low-frequency EXTASIS experiment, for instance. We present in this work a new formula for calculating the exact field emitted by a particle track in two semi-infinite media separated by a planar boundary. We also explore the validity of the far-field approximation and make some predictions for EAS using a simple shower model.

Filters for RFI suppression in AERA radio detection of cosmic rays

Radio stations can observe radio signals caused by coherent emissions due to geomagnetic radiation and charge excess processes mainly in the frequency band from 30 to 80 MHz. This range is often highly contaminated by human-made RFI. In order to improve the signal to noise ratio, RFI filters have to suppress this contamination.The paper compares several (currently in use and proposed) RFI filters used in the Auger Engineering Radio Array (AERA), being a part of the Pierre Auger Observatory. We analyzed both: the non-adaptive filter (IIR notch) as well as adaptive filters: IIR notch supported by the virtual NIOS® processor, FIR based on the linear prediction supported by the virtual NIOS® processor, the FIR fully implemented into FPGA fabric used the Levinson algorithm without any processor (all coefficients fully calculated in the FPGA logic elements) and finally the Delayed Least Mean Square filter also with a modification proposed by Harris, variable step size and Instantaneous LMS filter.We investigated: the efficiency of the several mono-carriers suppression, the distortion factors of cosmic rays pulses after filtering, the speed of the filter response as well as the power consumption crucial for systems supplied by solar panels.The 200 MW solar farm with 250 kV power line is anticipated to be built in the Southern part of the Auger array. High-power DC/AC converter for sure introduce a huge noise in the electromagnetic spectrum being a topic of interest of AERA. Very efficient, adaptive filter becomes a crucial issue. Simulations and laboratory measurement suggest that the most promising will be the Instantaneous Least Mean Square filter with dynamically modified input range.

Radio detection of cosmic rays with the Auger Engineering Radio Array

The Auger Engineering Radio Array (AERA) complements the Pierre Auger Observatory with 150 radio-antenna stations measuring in the frequency range from 30 to 80 MHz. With an instrumented area of 17 km2, the array constitutes the largest cosmic-ray radio detector built to date, allowing us to do multi-hybrid measurements of cosmic rays in the energy range of 1017 eV up to several 1018 eV. We give an overview of AERA results and discuss the significance of radio detection for the validation of the energy scale of cosmicray detectors as well as for mass-composition measurements.

The Least Mean Squares Adaptive FIR Filter for Narrow-Band RFI Suppression in Radio Detection of Cosmic Rays

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.

Adaptive IIR-Notch Filter for RFI Suppression in a Radio Detection of Cosmic Rays

Radio stations can observe radio signals caused by coherent emissions due to geomagnetic radiation and charge excess processes mainly in the frequency band from 30 to 80 MHz. This range is highly contaminated by human-made radio frequency interference (RFI). In order to improve the signal-to-noise ratio, RFI filters are used to suppress this contamination. Infinite impulse response (IIR)-notch filters operate with fixed parameters and suppress several narrow bands. IIR filters are generally potentially unstable due to feedbacks; however, they are much shorter and more power efficient than finite impulse response filters. We implemented an NIOS virtual processor calculating new set of IIR filter coefficients, which are reloaded dynamically on-the-fly. Spectrum analysis of the 30–80-MHz band can also be supported by the Altera IP Cores. The NIOS adjusts the new coefficients of the filter checking whether the poles are inside the unique complex radius (a condition of stability) as well as tuning the width of the notch filter. Practical implementation was tested in the laboratory with signal and pattern generators. Laboratory results are very promising. The IIR filter follows the drifting frequencies over very wide ranges (even 15 MHz for investigated range of 30–80 MHz), keeping a suppression factor on a very high level (≥10). The novelty of this paper is an introduction of the adaptive IIR-notch filter, which has not been used in any previous experiment.

Ultimate precision in cosmic-ray radio detection — the SKA

As of 2023, the low-frequency part of the Square Kilometre Array will go online in Australia. It will constitute the largest and most powerful low-frequency radio-astronomical observatory to date, and will facilitate a rich science programme in astronomy and astrophysics. With modest engineering changes, it will also be able to measure cosmic rays via the radio emission from extensive air showers. The extreme antenna density and the homogeneous coverage provided by more than 60,000 antennas within an area of one km$^2$ will push radio detection of cosmic rays in the energy range around 10$^{17}$ eV to ultimate precision, with superior capabilities in the reconstruction of arrival direction, energy, and an expected depth-of-shower-maximum resolution of 6~g/cm${^2}$.

Adaptive Linear Predictor FIR Filter Based on the Cyclone V FPGA With HPS to Reduce Narrow Band RFI in Radio Detection of Cosmic Rays

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.

A large light-mass component of cosmic rays at 10(17)-10(17.5) electronvolts from radio observations.

Cosmic rays are the highest-energy particles found in nature. Measurements of the mass composition of cosmic rays with energies of 10(17)-10(18) electronvolts are essential to understanding whether they have galactic or extragalactic sources. It has also been proposed that the astrophysical neutrino signal comes from accelerators capable of producing cosmic rays of these energies. Cosmic rays initiate air showers--cascades of secondary particles in the atmosphere-and their masses can be inferred from measurements of the atmospheric depth of the shower maximum (Xmax; the depth of the air shower when it contains the most particles) or of the composition of shower particles reaching the ground. Current measurements have either high uncertainty, or a low duty cycle and a high energy threshold. Radio detection of cosmic rays is a rapidly developing technique for determining Xmax (refs 10, 11) with a duty cycle of, in principle, nearly 100 per cent. The radiation is generated by the separation of relativistic electrons and positrons in the geomagnetic field and a negative charge excess in the shower front. Here we report radio measurements of Xmax with a mean uncertainty of 16 grams per square centimetre for air showers initiated by cosmic rays with energies of 10(17)-10(17.5) electronvolts. This high resolution in Xmax enables us to determine the mass spectrum of the cosmic rays: we find a mixed composition, with a light-mass fraction (protons and helium nuclei) of about 80 per cent. Unless, contrary to current expectations, the extragalactic component of cosmic rays contributes substantially to the total flux below 10(17.5) electronvolts, our measurements indicate the existence of an additional galactic component, to account for the light composition that we measured in the 10(17)-10(17.5) electronvolt range.

FPGA Based Wavelet Trigger in Radio Detection of Cosmic Rays

Experiments which show coherent radio emission from extensive air showers induced by ultra-high-energy cosmic rays are designed for a detailed study of the development of the electromagnetic part of air showers. Radio detectors can operate with 100 % up time as, e.g., surface detectors based on water-Cherenkov tanks. They are being developed for ground-based experiments (e.g., the Pierre Auger Observatory) as another type of air-shower detector in addition to fluorescence detectors, which operate with only ∼10 % of duty on dark nights. The radio signals from air showers are caused by coherent emission from geomagnetic radiation and charge-excess processes. The self-triggers in radio detectors currently in use often generate a dense stream of data, which is analyzed afterwards. Huge amounts of registered data require significant manpower for off-line analysis. Improvement of trigger efficiency is a relevant factor. The wavelet trigger, which investigates on-line the power of radio signals (∼V2/R), is promising; however, it requires some improvements with respect to current designs. In this work, Morlet wavelets with various scaling factors were used for an analysis of real data from the Auger Engineering Radio Array and for optimization of the utilization of the resources in an FPGA. The wavelet analysis showed that the power of events is concentrated mostly in a limited range of the frequency spectrum (consistent with a range imposed by the input analog band-pass filter). However, we found several events with suspicious spectral characteristics, where the signal power is spread over the full band-width sampled by a 200 MHz digitizer with significant contribution of very high and very low frequencies. These events may not originate from cosmic ray showers but could be the result of human contamination. The engine of the wavelet analysis can be implemented in the modern powerful FPGAs and can remove suspicious events on-line to reduce the trigger rate.

The Renaissance of Radio Detection of Cosmic Rays

Nearly 50 years ago, the first radio signals from cosmic ray air showers were detected. After many successful studies, however, research ceased not even 10 years later. Only a decade ago, the field was revived with the application of powerful digital signal processing techniques. Since then, the detection technique has matured, and we are now in a phase of transition from small-scale experiments accessing energies below 1018 eV to experiments with a reach for energies beyond 1019 eV. We have demonstrated that air shower radio signals carry information on both the energy and the mass of the primary particle, and current experiments are in the process of quantifying the precision with which this information can be accessed. All of this rests on a solid understanding of the radio emission processes which can be interpreted as a coherent superposition of geomagnetic emission, Askaryan charge-excess radiation, and Cherenkov-like coherence effects arising in the density gradient of the atmosphere. In this article, I highlight the "state of the art" of radio detection of cosmic rays and briefly discuss its perspectives for the next few years.

An Optimization of the FPGA Based Wavelet Trigger in Radio Detection of Cosmic Rays

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

FPGA/NIOS Implementation of an Adaptive FIR Filter Using Linear Prediction to Reduce Narrow-Band RFI for Radio Detection of Cosmic Rays

We present the FPGA/NIOS implementation of an adaptive finite impulse response (FIR) filter based on linear prediction to suppress radio frequency interference (RFI). This technique will be used for experiments that observe coherent radio emission from extensive air showers induced by ultra-high-energy cosmic rays. These experiments are designed to make a detailed study of the development of the electromagnetic part of air showers. Therefore, these radio signals provide information that is complementary to that obtained by water-Cherenkov detectors which are predominantly sensitive to the particle content of an air shower at ground. 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 discuss an adaptive filter which is based on linear prediction. The coefficients for the linear predictor (LP) are dynamically refreshed and calculated in the embedded NIOS processor, which is implemented in the same FPGA chip. The Levinson recursion, used to obtain the filter coefficients, is also implemented in the NIOS and is partially supported by direct multiplication in the DSP blocks of the logic FPGA segment. Tests confirm that the LP can be an alternative to other methods involving multiple time-to-frequency domain conversions using an FFT procedure. These multiple conversions draw heavily on the power consumption of the FPGA and are avoided by the linear prediction approach. Minimization of the power consumption is an important issue because the final system will be powered by solar panels. The FIR filter has been successfully tested in the Altera development kits with the EP4CE115F29C7 from the Cyclone IV family and the EP3C120F780C7 from the Cyclone III family at a 170 MHz sampling rate, a 12-bit I/O resolution, and an internal 30-bit dynamic range. Most of the slow floating-point NIOS calculations have been moved to the FPGA logic segments as extended fixed-point operations, which significantly reduced the refreshing time of the coefficients used in the LP. We conclude that the LP is a viable alternative to other methods such as non-adaptive methods involving digital notch filters or multiple time-to-frequency domain conversions using an FFT procedure.

FPGA Based Signal-Processing for Radio Detection of Cosmic Rays

For the observation of ultra high-energy cosmic rays (UHECRs) by the detection of their coherent radio emission an FPGA based trigger and radio frequency interference (RFI) filter was developed. Using radio detection, the electromagnetic part of an air shower in the atmosphere may be studied in detail, thus providing information complementary to that obtained by water Cherenkov detectors which are predominantly sensitive to the muonic content of an air shower at ground. For an extensive radio detector array, due to the limited communication data rate, a sophisticated self trigger is necessary. However, radio signals in the frequency range of 30-80 MHz are significantly contaminated by RFI and human made distortions. The digitized signals are converted from the time to frequency domain by a FFT procedure, then a deconvolution and RFI-filters are applied to correct the frequency response and to suppress the RFI. Finally the filtered data is transformed back into the time domain by an iFFT, also generating an envelope as a base for the final self-trigger. To avoid leakage effect and to create an overlap of successive data blocks, trapezoidal windowing is applied with internal overclocking. The algorithms for two polarization channels have been successfully implemented in a single FPGA and tested in a prototype board with 180 MHz sampling rate, 16-bit dynamic range, and 12-bit resolution.

Surrounding effects and sensitivity of the CODALEMA experiment

Future autonomous systems of cosmic ray radiodetection will be installed over large areas, encountering various environmental and noise conditions. It is thus essential to check and evaluate the influence of the vicinity on the sensitivity of detection. In this paper, the main environmental influences on the performances of the CODALEMA experiment are presented. It will be shown that the performances and sensitivity of the detector are not affected by the environment, and that the new CODALEMA autonomous detection station can reach the ultimate accessible sensitivity even in a quite noisy environment. This allows deconvolving the detector's response and recovering the real spectral characteristics of the cosmic ray air showers.