Radio Detection Research Articles

Lidar and Radar Enable the Next Generation of Dairy Cattle Feeding

HighlightsDevelopments in automatized feeding lead to farms being locked industrial production sites.LiDAR and Radar facilitate driverless feed mixers by covering navigation and safety aspects.External safety of driverless vehicles can be compensated with optical, acoustical and organizational measures.Abstract. Present automatic feeding systems (AFS) for dairy cattle are predominantly machines with additional external structures, e.g., bus bars and guide rails. In order to achieve complete automation of the feeding process, future AFS must be adaptable to different types of farm structures. Technologies such as LiDAR (Light Detection and Ranging) and Radar (Radio Detection and Ranging) enable free navigation of self-propelled feed mixer wagons and make important contributions to personal protection and collision avoidance. This enables the feed mixer to reach silo systems independently, remove feed and present it at the feed table. Using a self-propelled mixer feeder, both LiDAR and Radar are comparatively analyzed in a practical series of tests under farm conditions. Research into the legal framework and an exemplary risk assessment lay the conceptual basis for future automatic feeding systems. The aim of this consideration is to derive a coordinated concept for the areas of navigation and collision protection in an automatic feeding system for next-generation dairy cattle. Keywords: AFS, AGV, Automation, Dairy, Feeding, Laser, LiDAR, Radar.

Development of the ion cyclotron emission diagnostic on the HL-2A tokamak

An ion cyclotron emission (ICE) diagnostic, which is based on a B-dot probe, has been recently designed and installed on HL-2A tokamak. The diagnostic is used to study various high-frequency magnetic field fluctuations which can be excited by energetic ions and runaway electrons in the plasma. The ICE diagnostic on HL-2A includes a high-frequency B-dot probe, direct current (DC) block, radio frequency splitters, filter bank and power detectors. The filter bank is composed of 16 channels filters, with the center frequency covering from 10 to 160 MHz, 10 MHz step length and 8 MHz bandwidth. The log detectors with a large dynamic range (from −80 dBm to −20 dBm) are used to detect the bandpass power. Test results of the B-dot probe, filters and power detectors are shown. The signals can also be sampled with a fast analog-to-digital converter with a 14-bit depth, 100 MHz bandwidth and 250 MSample/s sampling rate.

Carbon based electronic technology in post-Moore era: progress, applications and challenges

In the past 60 years, silicon-based semiconductor technology has triggered off the profound change of our information society, but it is also gradually approaching to the physical limit and engineering limit as well. Thus, the global semiconductor industry has entered into the post-Moore era. Carbon nanotube has many excellent electronic properties such as high mobility and ultra-thin body, so it has become a hopeful candidate for the new semiconductor material in the post-Moore era. After more than 20 years of development, carbon based electronic technology has made fundamental breakthroughs in many basic problems such as material preparation, Ohmic metal-semiconductor contact and gate engineering. In principle, there is no insurmountable obstacle in its industrialization process now. Therefore, in this paper the intrinsic advantages of carbon based electronic technology in the post-Moore era is introduced, the basic problems, progress and optimization direction of carbon based electronic technology are summarized, the application prospects in the fields of digital circuits, radio frequency electronics, sensing and detection, three-dimensional integration and chips for special applications are presented. Finally, the comprehensive challenges to the industrialization of carbon based electronic technology are analyzed, and its future development is also prospected.

Логнормальная модель рассеяния радиоволн в сотовых сетях мобильной связи.

The main provisions of a stable deterministic model for calculating the attenuation of the average signal power during the propagation of radio waves in the decimeter range along a normal scattering surface are presented. The proposed model is based on the property of the lognormal distribution of variations in the average receiving power relative to the median level of the global power law of radio wave propagation and is designed to improve the accuracy and reliability of predicting the average signal attenuation along the earth's surface. The model can be used for high-precision calculation of radio coverage and detection of inter-cell interference in mobile cellular communication networks, and can also improve the accuracy of calculating radio relay communication lines.

UNMANNED AERIAL VEHICLE RADAR VISIBILITY ESTIMATION PROCEDURE DURING THE FLIGHT TEST

The calculation and accurate determination of the main indicator of radar visibility - radar cross-section is a complex problem for which theoretical and experimental methods have been developed.
 Theoretical methods for determining the radar cross-section at this time are quite accurate, but the priority area of research is still to determine the radar cross-section by the experimental method.
 One of such practical methods for determining the radar cross-section is a model (and for small unmanned aerial vehicles - full-scale) experiment in a anechoic screened chamber, but this experiment does not take into account the propagation properties of radio wave in real conditions.
 The most reliable characteristics of the unmanned aerial vehicle (UAV) radar visibility are obtained in a full- scale experiment during a testing ground experiment by test flight.
 Determination of the radar cross-section by the test flight method is carried out in real conditions under the influence of all available factors for the radio detection and location, methods of its processing, the presence of spurious reflection, the real jamming environment.
 A signals training area is used as a test range. A signals training area is an spatial region (sector of the terrain) where the instrumentation radar set and certain spatio measuring points arе located and the signal-noise-rate of the radar sеt receive path is measured when the unmanned aerial vehicle to be in the spatio measuring points.
 It should be noted that any radar set can be used as a instrumentation radar set, subject to conformity with the measurement accuracy meets the specified requirements.
 Given the above, the UAV radar visibility evaluation procedure during testing ground experiment by test flight allows to determine the radar cross-section in the absence of a perfect measuring system and provides a high level of measurement accuracy.

Polarization-converse tag design for clutter-isolation radio detection and ranging applications

Polarization-converse tag design for clutter-isolation radio detection and ranging applications

The MAVERIC Survey: The first radio and X-ray limits on the detached black holes in NGC 3201

ABSTRACT The Galactic globular cluster (GC) NGC 3201 is the first Galactic GC observed to host dynamically confirmed stellar-mass black holes (BHs), containing two confirmed and one candidate BH. This result indicates that GCs can retain BHs, which has important implications for GC evolution. NGC 3201 has been observed as part of the MAVERIC survey of Galactic GCs. We use these data to confirm that there is no radio or X-ray detection of the three BHs, and present the first radio and X-ray limits on these sources. These limits indicate that any accretion present is at an extremely low rate and may be extremely inefficient. In particular, for the system ACS ID #21859, by assuming the system is tidally locked and any accretion is through the capture of the companion’s winds, we constrain the radiative efficiency of any accretion to ≲ 1.5 × 10−5. We also combine the radio and X-ray source catalogues from the MAVERIC survey with the existing MUSE spectroscopic surveys and the HUGS catalogue of NGC 3201 to provide a catalogue of 42 multiwavelength sources in this cluster. We identify a new red straggler source with X-ray emission, and investigate the multiwavelength properties of the sub-subgiant population in the cluster.

Ionospheric vertical total electron content prediction model in low-latitude regions based on long short-term memory neural network

Ionosphere delay is one of the main sources of noise affecting global navigation satellite systems, operation of radio detection and ranging systems and very-long-baseline-interferometry. One of the most important and common methods to reduce this phase delay is to establish accurate nowcasting and forecasting ionospheric total electron content models. For forecasting models, compared to mid-to-high latitudes, at low latitudes, an active ionosphere leads to extreme differences between long-term prediction models and the actual state of the ionosphere. To solve the problem of low accuracy for long-term prediction models at low latitudes, this article provides a low-latitude, long-term ionospheric prediction model based on a multi-input-multi-output, long-short-term memory neural network. To verify the feasibility of the model, we first made predictions of the vertical total electron content data 24 and 48 hours in advance for each day of July 2020 and then compared both the predictions corresponding to a given day, for all days. Furthermore, in the model modification part, we selected historical data from June 2020 for the validation set, determined a large offset from the results that were predicted to be active, and used the ratio of the mean absolute error of the detected results to that of the predicted results as a correction coefficient to modify our multi-input-multi-output long short-term memory model. The average root mean square error of the 24-hour-advance predictions of our modified model was 4.4 TECU, which was lower and better than 5.1 TECU of the multi-input-multi-output, long short-term memory model and 5.9 TECU of the IRI-2016 model.

MeerKAT radio detection of the Galactic black hole candidate Swift J1842.5−1124 during its 2020 outburst

ABSTRACT Swift J1842.5−1124 is a transient Galactic black hole X-ray binary candidate, which underwent a new outburst in 2020 May. We performed multi-epoch MeerKAT radio observations under the ThunderKAT large survey programme, coordinated with quasi-simultaneous Swift/XRT X-ray observations during the outburst, which lasted nearly a month. We were able to make the first-ever radio detection of this black hole binary with the highest flux density of 229 ± 31 $\mu$Jy when the source was in the hard state, after non-detection in the radio band in the soft state which occurred immediately after its emergence during the new X-ray outburst. Therefore, its radio and X-ray properties are consistent with the disc-jet coupling picture established in other black hole X-ray binaries. We place the source’s quasi-simultaneous X-ray and radio measurements on the radio/X-ray luminosity correlation plane; two quasi-simultaneous radio/X-ray measurements separated by 11 d were obtained, which span ∼2 dex in the X-ray luminosity. If the source follows the black hole track in the radio/X-ray correlation plane during the outburst, it would lie at a distance beyond ∼5 kpc.

Detection of radio signals against the background of strong electromagnetic noise in transport

The problem of detecting a useful signal in the presence of a strong background noise is considered. To solve it, a statistical approach is used, based on a change in the level of chaos in the system when an additional random or deterministic process occurs, which is probabilistically independent from a set of stochastic phenomena that form background noise. It is shown that the occurrence of this process changes the level of entropy of the measured signal; this fact is the basis of the applied mathematical algorithm. It is based on the elements of the Fourier transform apparatus for the probability density with an appropriate choice of a nonlinear function of the random process under study. The proposed approach, based on variations in the randomness in the system in the presence of a useful signal, makes it possible to record its presence against the background of noise components even at low signal-to-noise ratios. The effectiveness of the method is confirmed both by theoretical justification and by the calculations presented in this work. The condition for the implementation of the technique described in the article, which does not impose restrictions on the studied physical fields and frequency ranges, is the comparability of the width of the probabilistic distribution of the desired useful signal with several intervals of discreteness of the measuring equipment. One of the results of this work is a high sensitivity to the emergence of independent random components.

The detection of radio emission from known X-ray flaring star EXO 040830−7134.7

ABSTRACT We report the detection of radio emission from the known X-ray flaring star EXO 040830−7134.7 during Karoo Array Telescope (MeerKAT) observations of the nearby cataclysmic variable VW Hydri. We have three epochs of MeerKAT observations, where the star is not detected in the first epoch, is detected in the second epoch, and is marginally detected in the third epoch. We cannot distinguish whether the detection is quiescent emission or a transient radio burst. If we assume that the radio detection is quiescent emission, the source lies somewhat to the right of the Güdel–Benz relation; however, if we assume that the upper limit on the radio non-detection is indicative of the quiescent emission, then the source lies directly on the relation. Both cases are broadly consistent with the relation. We use archival spectral energy distribution data and new Southern African Large Telescope high-resolution spectroscopy to confirm that EXO 040830−7134.7 is a chromospherically active M-dwarf with a temperature of 4000 ± 200 K of spectral type M0V. We use All-Sky Automated Survey (ASAS), All-Sky Automated Survey for Supernovae (ASAS-SN), and Transiting Exoplanet Survey Satellite (TESS) optical photometry to derive an improved rotational period of 5.18 ± 0.04 d. This is the first radio detection of the source, and the first MeerKAT detection of an M-dwarf.

A Systematic Search for Dual Active Galactic Nuclei in Merging Galaxies (ASTRO-DARING) II: First Results from Long-slit Spectroscopic Observations

Abstract Building a large sample of kiloparsec (kpc)-scale dual active galactic nuclei (AGNs) among merging galaxies is of vital importance to understand the coevolution between host galaxies and their central super massive black holes (SMBHs). Doing so, with just such a sample, we have developed an innovative method of systematically searching and identifying dual AGNs among kpc-scale merging galaxies and selected 222 candidates at redshifts ≤ 0.25. All the selected candidates have radio detection in the Faint Images of the Radio Sky at Twenty Centimeters survey and at least one of two cores previously revealed as AGN spectroscopically. We report the first results from a systematic search for dual AGNs in merging galaxies (ASTRO-DARING), which consist of spatially resolved long-slit spectroscopic observations of 41 targets selected from our merging galaxies sample carried out between 2014 November and 2017 February, using the Yunnan Faint Object Spectrograph and Camera mounted on the 2.4 meter telescope in Lijiang of Yunnan Observatories. Of these, 16 are likely dual AGNs, and 15 are newly identified. The efficiency of ASTRO-DARING is thus nearly 40%. With this method, we plan to build the first even sample of more than 50 dual AGNs constructed using a consistent approach. Further analysis of the dual AGN sample shall provide vital clues for understanding the coevolution of galaxies and SMBHs.

Adversarial Examples Detection of Radio Signals Based on Multifeature Fusion

In the field of deep learning, deep neural networks (DNNs) have shown good performance on classification applications. However, a DNN model is vulnerable to adversarial examples, which is formed by adding tiny perturbations on a normal example and can mislead the DNN model to make a wrong estimate during the prediction. In this brief, for adversarial attacks in radio signals field, we propose a novel adversarial example detection strategy based on multifeature fusion and provide a framework which includes generating adversarial examples, extracting the local intrinsic dimensionality (LID) features and the constellation diagram (CD) features, detecting adversarial examples. We obtain the output values of normal examples and adversarial examples in each layer of the model respectively, and then, calculate the LID features values of examples by the maximum likelihood estimate based on a certain neighborhood range. Meanwhile, we calculate the CD features values by the range feature and density feature of the constellation diagram distribution. Finally, a logistic regression classifier is trained based on multifeature fusion values to detect adversarial examples. The experimental results across two benchmark datasets demonstrate that the proposed multifeature fusion method could accurately detect adversarial examples of radio signals. The detection accuracy is up to 98.7% when the perturbation reached 10%.

Radio interferometry applied to the observation of cosmic-ray induced extensive air showers

We developed a radio interferometric technique for the observation of extensive air showers initiated by cosmic particles. In this proof-of-principle study we show that properties of extensive air showers can be derived with high accuracy in a straightforward manner. When time synchronisation below sim 1 ns between different receivers can be achieved, direction reconstruction resolution of < 0.2^circ and resolution on the depth of shower maximum of <10 g/cm^2 are obtained over the full parameter range studied, with even higher accuracy for inclined incoming directions. In addition, by applying the developed method to dense arrays of radio antennas, the energy threshold for the radio detection of extensive air showers can be significantly lowered. The proposed method can be incorporated in operational and future cosmic particle observatories and with its high accuracy it has the potential to play a crucial role in unravelling the composition of the ultra-high-energy cosmic-particle flux.

Probing the Wind Component of Radio Emission in Luminous High-redshift Quasars

Abstract We discuss a probe of the contribution of wind-related shocks to the radio emission in otherwise radio-quiet quasars. Given (1) the nonlinear correlation between UV and X-ray luminosity in quasars, (2) that such a correlation leads to higher likelihood of radiation-line-driven winds in more luminous quasars, and (3) that luminous quasars are more abundant at high redshift, deep radio observations of high-redshift quasars are needed to probe potential contributions from accretion disk winds. We target a sample of 50 z ≃ 1.65 color-selected quasars that span the range of expected accretion disk wind properties as traced by broad C iv emission. 3 GHz observations with the Very Large Array to an rms of ≈10 μJy beam−1 probe to star formation rates of ∼400 M ⊙ yr−1, leading to 22 detections. Supplementing these pointed observations are survey data of 388 sources from the LOFAR Two-meter Sky Survey Data Release 1 that reach comparable depth (for a typical radio spectral index), where 123 sources are detected. These combined observations reveal a radio detection fraction that is a nonlinear function of C iv emission-line properties and suggest that the data may require multiple origins of radio emission in radio-quiet quasars. We find evidence for radio emission from weak jets or coronae in radio-quiet quasars with low Eddington ratios, with either (or both) star formation and accretion disk winds playing an important role in optically luminous quasars and correlated with increasing Eddington ratio. Additional pointed radio observations are needed to fully establish the nature of radio emission in radio-quiet quasars.

The Simultaneous Localization and Mapping (SLAM)-An Overview

Positioning is a need for many applications related to mapping and navigation either in civilian or military domains. The significant developments in satellite-based techniques, sensors, telecommunications, computer hardware and software, image processing, etc. positively influenced to solve the positioning problem efficiently and instantaneously. Accordingly, the mentioned development empowered the applications and advancement of autonomous navigation. One of the most interesting developed positioning techniques is what is called in robotics as the Simultaneous Localization and Mapping SLAM. The SLAM problem solution has witnessed a quick improvement in the last decades either using active sensors like the RAdio Detection And Ranging (Radar) and Light Detection and Ranging (LiDAR) or passive sensors like cameras. Definitely, positioning and mapping is one of the main tasks for Geomatics engineers, and therefore it's of high importance for them to understand the SLAM topic which is not easy because of the huge documentation and algorithms available and the various SLAM solutions in terms of the mathematical models, complexity, the sensors used, and the type of applications. In this paper, a clear and simplified explanation is introduced about SLAM from a Geomatical viewpoint avoiding going into the complicated algorithmic details behind the presented techniques. In this way, a general overview of SLAM is presented showing the relationship between its different components and stages like the core part of the front-end and back-end and their relation to the SLAM paradigm. Furthermore, we explain the major mathematical techniques of filtering and pose graph optimization either using visual or LiDAR SLAM and introduce a summary of the deep learning efficient contribution to the SLAM problem. Finally, we address examples of some existing practical applications of SLAM in our reality.

Simulator use on competence

Utilization of a bridge simulator that provides an accurate picture of conditions such as on the bridge of a ship to increase the competence that is incorporated in the navigation function. This survey research takes samples from the population and uses a questionnaire as the primary data collection instrument. The sample used in this study was cadets majoring in marine engineering at the Makassar Shipping Science Polytechnic campus. Collecting data using the questionnaire method, and for data analysis by simplifying all data and then presenting it in a systematic arrangement, after that interpreting or interpreting the data obtained. By practicing using a simulator, cadets can practice and understand the function of the material whose scope is about Radar (radio detection &amp; ranging), AIS (Automatic Identification System), GPS, and ECDIS.

The Simultaneous Localization and Mapping (SLAM)-An Overview

Positioning is needed for many applications related to mapping and navigation, either in civilian or military domains. The significant developments in satellite-based techniques, sensors, telecommunications, computer hardware and software, image processing, etc. positively influenced solving the positioning problem efficiently and instantaneously. Accordingly, the mentioned development empowered the applications and advancement of autonomous navigation. One of the most interestingly developed positioning techniques is what is called in robotics Simultaneous Localization and Mapping (SLAM). The SLAM problem solution has witnessed a quick improvement in the last decades, either using active sensors like the RAdio Detection and Ranging (Radar) and Light Detection and Ranging (LiDAR) or passive sensors like cameras. Definitely, positioning and mapping is one of the main tasks for geomatics engineers, and therefore it's of high importance for them to understand the SLAM topic, which is not easy because of the huge documentation and algorithms available and the various SLAM solutions in terms of the mathematical models, complexity, the sensors used, and the type of applications. In this paper, a clear and simplified explanation of SLAM from a geometrical viewpoint is introduced, avoiding going into the complicated algorithmic details behind the presented techniques. In this way, a general overview of SLAM is presented, showing the relationship between its different components and stages, like the core part of the front-end and back-end, and their relation to the SLAM paradigm. Furthermore, we explain the major mathematical techniques of filtering and pose graph optimization, either using visual or LiDAR SLAM, and introduce a summary of the efficient contribution of deep learning to the SLAM problem. Finally, we address examples of some existing practical applications of SLAM in our reality.

Soil exploration using ground penetrating radar

Geophysical methods are extensively utilized in the field of geology and in geotechnical engineering such as seismic, gravitational, magnetic and electromagnetic fields. These methods are used to locate or to understand conditions below the ground surface, and the physical properties of subsurface. GPR also known as Radio Detecting and Ranging is based on the electromagnetic waves. It is a specially designed radar unit for transmitting electromagnetic pulses below the ground instead of air. In GPR the medium is soil which is heterogeneous and has higher attenuation rate than air. This method is used to measure the length, depth or to locate the soil layers and its deposits. GPR is one of the most versatile sensors; it provides high resolution profiles for shallow depth. GPR has been used in diverse fields such as archaeology, non-destructive testing, probing underground caves, detecting landmines, mapping pipes and conduits, investigating the reinforcement and conditions of roads, bridges and airport runways, to name a few. Use of this technique/method is being extensively adopted from recent years because of its properties and vast applications. The main applications of GPR in subsurface mapping are: mapping of subsurface utility structures, detection and mapping of unexploded ordnance and mines, extraction of hazardous waste containers or unexploded ammunitions, maintenance or repair of subsurface structures. This paper presents an understanding of the concept or the need of GPR dedicated to civil engineering applications in general and in the field of geotechnical engineering in particular.

First Discovery of New Pulsars and RRATs with CHIME/FRB

Abstract We report the discovery of seven new Galactic pulsars with the Canadian Hydrogen Intensity Mapping Experiment’s Fast Radio Burst (CHIME/FRB) backend. These sources were first identified via single pulses in CHIME/FRB, then followed up with CHIME/Pulsar. Four sources appear to be rotating radio transients, pulsar-like sources with occasional single-pulse emission with an underlying periodicity. Of those four sources, three have detected periods ranging from 220 ms to 2.726 s. Three sources have more persistent but still intermittent emission and are likely intermittent or nulling pulsars. We have determined phase-coherent timing solutions for the latter two. These seven sources are the first discovery of previously unknown Galactic sources with CHIME/FRB and highlight the potential of fast radio burst detection instruments to search for intermittent Galactic radio sources.