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A study examined the ability of 32 grade-5 students in Alberta (Canada) to interpret Radarsat satellite radar images. The students were able to interpret most elements of the images, but working directly with the CD-ROM proved too difficult for them. The Radarsat images have limited value as a geographic resource at the grade-5 level. (TD)

Argues that Radarsat satellite images should be used in elementary classrooms to teach geography. Studies the abilities of children to interpret features of a Radarsat image. Shows that they can interpret major geographical features on the image but had problems finding Radarsat locations on road maps. (DSK)

Describes the first moon-radar echo experiment conducted by Zoltan Bay in Hungary and comments on Bay as a model for contemporary physics education. (DDR)

Numerous radio stations across the nation perform nonbroadcast services in areas ranging from aviation, forestry protection, and telephone maintenance to amateur and citizen radio. These services can be grouped in four general categories: (1) safety, (2) industry, (3) land transportation, and (4) miscellaneous purposes. This bulletin briefly describes some 50 radio services which comprise the Safety and Special Radio Services, and FCC (Federal Communications Commission) regulations for these stations. (SC)

The discovery of radio waves, infrared, and x-rays and their importance in describing the universe and its origins is discussed. Topics include radio waves from space, the radio pioneers of World War II, radio telescopes, infrared radiation, satellites, space missions, and x-ray telescopes. (KR)

Describes the Canadian Radarsat Satellite and remote sensing in order to demonstrate that teachers can incorporate this technology into the classroom. Maintains that third, fourth, fifth, and sixth grade students can understand and interpret remote sensing images and Landsat images. Provides a list of teaching resources other than the expensive Radarsat CD-ROMs. (CMK)

Suggests how to use remote sensing techniques and data in geography courses in high school and college as well as in geography research. Tips are presented on using techniques such as topographic maps, vertical aerial photographs in stereo pairs, satellite images, and SLAR images (which are particularly useful in teaching landforms and geomorphology). (DB)

Presents a description of the world's largest radio/radar antenna, the Areciba Observatory in Puerto Rico. Activities at the observatory are discussed as well as the scientific research in the field of radio astronomy. (SA)

Describes the nature, history, and applications of Doppler radar detecting the speed of moving object. Gives an example of measuring the radial velocity of a scattered wave. (YP)

Aiming at the large-scale application of metasurface in the field of radar stealth, we present a hybrid resonance-based and dispersion substrate integrated checkerboard metasurface (CMS) for reducing the radar cross section (RCS) of flat metallic targets. Considering the frequency-dependent characteristics of such a dispersion material, a pair of single and dual resonant artificial magnetic conductor meta-atoms with the modified "crusades-like" cell topologies is employed to maximize the operating bandwidth; besides, a comprehensive and thorough investigation on the resonance mechanism is conducted in this paper to provide an intuitive physical insight of meta-atoms' reflection responses. By comparing the predicted results with simulations, the quasi-periodic effect is introduced to explain the frequency shift of 10 dB RCS reduction bandwidth. In the implementation procedure, a prototype of the designed RCS reducer with a total dimension of 180 × 180 mm2 is fabricated and measured, the 10 dB RCS reduction bandwidth of theoretical simulation and experimental measurement are basically consistent, and the performance improvement of 8 dB RCS reduction in the experimental results can be attributed to the dispersion effects of the dielectric substrate. With a better figure of merit, our efforts may serve as a useful exemplar for the economical CMS architecture in radar evasive applications. [ABSTRACT FROM AUTHOR]

Accurate precipitation monitoring is crucial for understanding climate change and rainfall-driven hazards at a local scale. However, the current suite of monitoring approaches, including weather radar and rain gauges, have different insufficiencies such as low spatial and temporal resolution and difficulty in accurately detecting potentially destructive precipitation events such as hailstorms. In this study, we develop an array-based method to monitor rainfall with seismic nodal stations, offering both high spatial and temporal resolution. We analyze seismic records from 1825 densely spaced, high-frequency seismometers in Oklahoma, and identify signals from nine precipitation events that occurred during the one-month station deployment in 2016. After removing anthropogenic noise and Earth structure response, the obtained precipitation spatial pattern mimics the one from a nearby operational weather radar, while offering higher spatial (~ 300 m) and temporal (

The data fusion of radar and automatic dependent surveillance-broadcast(ADS-B) is the effective method to surveille the 'black flights' and flying birds. However, the tracking performance of the two sensors has large differences and is easy to be fluctuated, which will bring a decline in fusion accuracy. A data fusion method of radar and ADS-B based on track quality assessment is proposed. Firstly, the effects of local track accuracy, data update times and sensor measurement errors on local track quality on corresponding assessment factors are analyzed and quantified. And then, these assessment factors are combined to calculate the quality weighting factors of the local track, and the asynchronous track fusion processing of radar and ADS-B is completed based on the distributed fusion structure. Finally, the feasibility and effectiveness of the proposed method is verified with simulation experiment and application. The results show that the proposed fusion method can effectively improve the fusion accuracy, and the tracking errors are better than the traditional algorithms when the sensor tracking performance fluctuates.

Equivalent-time sampling can improve measurement or sensing systems because it enables a broader frequency band and higher delay resolution for periodic signals with lower sampling rates than a Nyquist receiver. Meanwhile, a digital down-conversion (DDC) technique can be implemented using a straightforward radio frequency (RF) circuit. It avoids timing skew and in-phase/quadrature gain imbalance instead of requiring a high-speed analog-to-digital converter to sample an intermediate frequency (IF) signal. Therefore, when equivalent-time sampling and DDC techniques are combined, a significant synergy can be achieved. This study provides a parameter design methodology for optimal equivalent-time sampling using DDC.

Abstract The increasing number of space objects (SO), debris, and constellation of satellites in Low Earth Orbit poses a significant threat to the sustainability and safety of space operations, which must be carefully and efficiently addressed to avoid mutual collisions. The space situational awareness is currently addressed by an ensemble of radar and radio‐telescopes that detect and track SO. However, a large part of space debris is composed of very small and tiny metallic objects, very difficult to detect. The authors demonstrate the benefits of using deep learning (DL) architectures for small space object detection by radar observations. TIRA radio telescope has been simulated to generate range‐Doppler maps, then used as inputs for object detection exploiting You‐Only‐Look‐Once (YOLO) frameworks. The results demonstrate that the object detection by using YOLO algorithms outperform conventional target detection approaches, thus indicating the potential benefits of using DL techniques for space surveillance applications.

Abstract Detection of space objects is a key component of space situational awareness, which could help prevent and minimise space collisions. While there have been lots of radar systems designed to detect space objects, few of them have dealt with long baseline distributed bistatic pairs. The authors focus on the feasibility of long baseline bistatic radars, which can be extended for the multistatic case; and the performance of the multistatic system for a target at different altitudes assuming one transmitter over three different scenarios: a cluster of receivers, receivers spread throughout the world and the combination of the two previous cases. To analyse the performance the multiple‐input‐multiple‐output (MIMO) ambiguity function (AF) will be employed. The results of the MIMO AF show how the fusion of different bistatic pairs improves the detection capabilities. Moreover, when the different radar measurements are coherently summed in the MIMO AF, the uncertainty on the location of the target is reduced.

Abstract Unmanned Aerial Vehicles, or drones, pose a significant threat to privacy and security. To understand and assess this threat, classification between different drone models and types is required. One way in which this has been demonstrated experimentally is through this use of micro‐Doppler information from radars. Classifiers capable of exploiting differences in micro‐Doppler spectra will require large amounts of data but obtaining such data experimentally is expensive and time consuming. The authors present the methodology and results of a drone micro‐Doppler simulation framework which uses accurate 3D models of drone components to yield detailed and realistic synthetic micro‐Doppler signatures. This is followed by the description of a purpose‐built validation radar that has been developed specifically to gather high‐fidelity experimental drone micro‐Doppler data with which is used to validate the simulation. Detailed comparisons between the experimental and simulated micro‐Doppler spectra from three models of drones with differently shaped propellers are given, showing very good agreement. The aim is to introduce the simulation methodology. Validation using single propeller micro‐Doppler is provided, although the simulation can be extended to multiple propellers. The simulation framework offers the potential to generate large quantities of realistic drone micro‐Doppler signatures for training classification algorithms.

Abstract For the integration detection of near space hypersonic weak targets by high pulse repetition frequency (PRF) radar, a novel method named Multi‐Hypothesis Fuzzy‐Matching Radon transform (MHFM‐RT) is proposed for the near space hypersonic target detection and tracking. For remote hypersonic target detection, to avoid range ambiguity, current radars always use a low PRF mode, which limit the number of pulse accumulations. Using the high PRF mode, the fuzzy folding will appear in the target range measurements when target trajectory crosses range fuzzy intervals. Therefore, there is a contradiction between range ambiguity and energy accumulation. The proposed method is used to match the fuzzy measurements, so as to realise the correct integration in the condition of range ambiguity. Firstly, considering the need of range ambiguity resolution, the mode of staggered PRF is used. Secondly, the first frame measurements are periodically extended for multiple‐fuzzy hypothesis. Finally, the weak target track is accumulated in MHFM‐RT domain, and the signal integration and ambiguity resolution can be realised simultaneously. The proposed method expands the Variable‐Diameter‐Arc‐Helix Radon transform (VDAH‐RT) method to fuzzy folding conditions. Compared with the existing methods, for 7‐scan measurements non‐coherent integration, the detection sensitivity of the proposed method is about 0.5–1 dB higher than that of the IMM hybrid filter algorithm, and about 1 dB higher than that of the RHT‐TBD approach, and it needs less storage space and has higher detection probability.

Abstract With the development of electronic warfare, anti‐jamming measure becomes more and more complex. There have been certain research results on jamming strategies, but only a few research materials on anti‐jamming strategies. It is difficult to simulate the real jamming environment, and there is no appropriate anti‐jamming decision‐making model for research. Cognitive radar can perceive the environment and receive feedback, which provides the possibility to solve the problem of anti‐jamming decision‐making. This article regards the anti‐jamming measure as a kind of interaction behaviour and establishes the cognitive radar antagonistic environment model and uses the reinforcement learning algorithm to solve the problem of anti‐jamming decision‐making. Finally, this article verifies the feasibility of applying reinforcement learning theory on making anti‐jamming decision in the radar antagonistic environment model. The performance of different reinforcement learning algorithms is compared, and their advantages and disadvantages are discussed.

A long-standing problem in meteor science has been the persistent presence of bias in the measured value of atmospheric scale heights obtained from radio meteor echoes. A common practice of fitting a linear function for bias correction follows the assumption that the systematic bias is devoid of seasonal asymmetry. This would be true if the mass and the velocity distribution of meteoroids remain invariant, both spatially and temporally. But so far no such convincing evidence has been published. On the contrary, fundamental arguments suggest that a universal mass function of radio meteoroids is counterintuitive. This parameter cannot remain invariant due to the intrinsic variability in the meteor response function resulting from the Earth's motion on the plane of ecliptic. In this paper, we show that an inverse relation exists between the width of meteor height distribution, expressed in unit of atmospheric scale height, and the exponent of the mass function. The overall mean of this exponent for the Sodankylä radar is |$1.91 \pm 0.02$|⁠ , modulated by a seasonal variation from the mean of the order of |$\sim \pm 0.1$|⁠. The stated inverse relation is applied to correct for the effect of mass distribution on the height distribution. Allowing for variable mass correction effectively removes the non-linear bias in the measured scale heights in the meteor ionization region. [ABSTRACT FROM AUTHOR]

Since 2021, a new surge in discrete aurora detections at Mars has been observed by the Emirates Mars Ultraviolet Spectrometer (EMUS) onboard the Emirates Mars Mission (EMM) Hope Orbiter as EMUS started to regularly obtain synoptic auroral images with a high sensitivity. Here we report on a fortuitous conjunction between EMM and Mars Express (MEX) using far ultraviolet (FUV) imaging of discrete aurora by EMM EMUS, in situ measurements of suprathermal electrons by the MEX Analyzer of Space Plasma and Energetic Atoms Electron Spectrometer (ELS), and topside radar sounding of the nightside ionosphere by the MEX Mars Advanced Radar for Subsurface and Ionosphere Sounding (MARSIS). In this event, EMM EMUS imaged a clear discrete aurora signature around moderately strong crustal magnetic fields on the nightside near the dusk terminator, 11 min before which MEX MARSIS measured a prominent local enhancement of the peak electron density in the nightside ionosphere and MEX ELS observed an in situ enhancement of suprathermal electrons at the corresponding location. A remarkable geographic agreement is found between the enhancements of the aurora, ionosphere, and suprathermal electrons, suggesting that the enhanced ionization and auroral emission are caused concurrently by precipitating suprathermal electrons. Subsequent images indicate that the discrete aurora slightly changed its shape in 15 min and mostly disappeared in a few hours. The MEX MARSIS measurements of the auroral ionosphere display overlapping ionospheric and surface echoes indicative of horizontal gradients of the peak electron density. Analysis of the overlapping echoes implies that the auroral ionosphere and electron precipitation could be highly structured with horizontal spatial scales on the order of several tens of km. MEX MARSIS also observed a non-auroral ionospheric enhancement with a wider spatial extent than the local auroral enhancement, suggesting alternative sources of the enhanced nightside ionosphere such as plasma transport. The comparison between the ionospheric structures measured by MEX MARSIS, suprathermal electron flux measured by MEX ELS, and discrete auroral emission imaged by EMM EMUS underscores the complexity of the auroral and non-auroral nightside ionospheres. This motivates further investigations of their sources, transport, and connections to the magnetotail dynamics of Mars. [ABSTRACT FROM AUTHOR]

In this paper, we present the results of a special experimental study of quiet-time behavior of the mid-latitude ionosphere over Eastern Europe by synchronously operation of different ground-based facilities. For the first time we used data obtained from Kharkiv incoherent scatter (IS) radar, ionosonde and coherent Doppler HF sounding system to detect and investigate traveling ionospheric disturbances (TIDs). The periods close to winter solstice and autumn equinox in 2018 were analyzed. The dominant periods and horizontal phase velocities of registered TIDs were 45–80 min and 230–460 m s−1, respectively. The strongest signatures were observed in the solstice measurement and represented by large amplitudes. Based on results obtained by all three methods, we found the LS TIDs with the same interval of time and altitude of propagation and similar characteristics (the period of about 50 min, estimated vertical 80 m/s and horizontal 460 m/s velocity and horizontal spatial scale size about 1360 km) for winter measurement. Such observational findings confirm the reliability of these TID detection techniques. Possible sources of TIDs generation were considered including solar terminator. [ABSTRACT FROM AUTHOR]

This paper introduces a machine-learning-driven approach for automated Nocturnal Low-Level Jet (NLLJ) identification using observations of wind profiles from a Radar Wind Profiler (RWP). The work discussed here is an effort to lay the groundwork for a systematic study of the Mid-Atlantic NLLJ's formation mechanisms and their influence on nocturnal and diurnal air quality in major urban regions by establishing a general framework of NLLJ features and characteristics with an identification algorithm. Leveraging a comprehensive wind profile dataset maintained by the Maryland Department of Environment's RWP network, our methodology employs supervised machine learning techniques to isolate the features of the south-westerly NLLJ. This methodology was developed to illuminate spatiotemporal patterns and nuanced characteristics of NLLJ events, unveiling their significant role in shaping the planetary boundary layer. This paper discusses the construction of this methodology, its performance against known NLLJs in the current literature, intended usage, and a preliminary statistical analysis. First light results from this analysis have identified a total of 90 south-westerly NLLJs from May–September of 2017–2021 as captured by the RWP stationed in Beltsville, MD (39.05°, -76.87°, 135 m ASL). A composite of these 90 jets is presented to better illustrate many of the bulk parameters, such as core height, duration, and maximum wind speed, associated with the onset and decay of the Mid-Atlantic NLLJ. We hope our study equips researchers and policymakers with further means to monitor, predict, and address these nocturnal dynamics phenomena that frequently influence boundary layer composition and air quality in the U.S. Mid-Atlantic and Northeastern regions. [ABSTRACT FROM AUTHOR]