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Space‐time coding metasurfaces (STCMs) have gained a great deal of achievements in the fields of radar and communication, but they have rarely been explored in the field of electronic jamming. The existing researches use time‐varying surface or phase‐switched screens to realize electronic deceptions, but the deceptions are completely passive and are limited in the time‐frequency domain. Here, a mechanism of STCM‐based deceptions is presented in the space and the time‐frequency domains, and precise designs of the STCM‐based deceptions are achieved by performing shifting operations on the space‐time coding sequences of the STCM. Moreover, STCM‐based DOA (direction‐of‐arrival) estimation is integrated with the deception procedure to achieve trackable electronic deception which cannot be realized by completely passive electronic jamming. A prototype system of the STCM‐based deception is built to verify the deception performance, and the experimental results agree well with the numerical simulations. This work extends the research and the applications of the STCMs, hence showing great scientific and engineering significance. [ABSTRACT FROM AUTHOR]

This study examines the differences related to microphysical properties of ice in thunderstorms over the Amazon and Congo Basin using the Precipitation Feature (PF) data sets derived from passive microwave and radar observations from the Tropical Rainfall Measuring Mission and Global Precipitation Mission Core Satellites. Analysis reveals that Amazon thunderstorms are likely composed of ice crystals smaller but more numerous than those in the Congo Basin, resulting in half as many flashes per PF on average in the Amazon, for similar Ice Water Content (IWC) or Area of 30 dBZ at −10°C (Acharge). The increase of the flash count following an increase of the IWC (Acharge) is only 72% (61%) as effective in the Amazon as it would be in the Congo Basin area. PFs with similar 30 dBZ radar echo top heights exhibit lower Brightness Temperatures (TBs) in the 85/89, 165, and 183 GHz frequencies over the Amazon, indicating more numerous smaller ice particles compared to those over the Congo Basin, which tend to show colder TBs at 37 GHz, possibly due to more numerous large graupel or hail particles. Comparisons of TBs in PFs with similar 30 dBZ echo top temperature between the Amazon and 3 × 3º global grids show that the median TB in Amazon is higher than that in most oceanic areas but is comparable to areas having high oceanic lightning activity (e.g., South Pacific Convergence Zone). It suggests that systems in the Amazon have similarities with maritime precipitation systems, yet with distinct characteristics indicative of land systems. Plain Language Summary: A comparison is made between Amazon (AM) and Congo Basin (CB) thunderstorms with similar reflectivity values seen by either TRMM or GPM, versus other variables that can help us understand the ice microphysics of these storms (IWC, area of 30 dBZ at −10C, Flash count, TBs). The radar reflectivity being driven by number and size (to the sixth power) of hydrometeors, the hypothesis is that for two storms with a same reflectivity value, one in AM and one in CB, the reflectivity value measured is driven by a higher concentration of large ice particles in CB (i.e., driven by size), while it is driven by a higher concentration of smaller ice particles in AM (i.e., driven by number). We quantify the lightning count difference between the two areas as a function of the amount of ice in the thunderstorm. It shows that AM produces significantly less lightning than CB on average for a similar ice content. Radiometers from TRMM and GPM are then used to compare the median TBs observed in the Amazon with the rest of the globe, to emphasize once again that AM is producing systems that are neither of land nor oceanic nature, but somewhere in the middle. Key Points: Amazonian systems are principally composed of smaller and more numerous ice crystalsIncreasing the Ice Water Content (IWC) and/or core size of thunderstorms in the Amazon demonstrates lower effectiveness in boosting lightning activityAmazonian systems present brightness temperatures unlike land or oceans but similar to oceanic regions with greater lightning activity [ABSTRACT FROM AUTHOR]

A large tornado and severe hailstorm struck Jersey, Channel Islands, just before midnight on 1–2 November 2023. Radar data are analysed to explore the morphology of the parent supercell thunderstorm. A tornado debris cloud was evident in polarimetric fields, collocated with a reflectivity ‘debris ball’. The debris cloud comprised a small region of exceptionally low correlation coefficient (<0.8) collocated with differential reflectivity ≤0dB. In vertical section, the debris signature comprised a column of low correlation coefficient and high reflectivity that tilted north‐northeast with height and extended to at least 2km above ground level. [ABSTRACT FROM AUTHOR]

Mars' polar ice deposits are thought to preserve a record of climate throughout their evolution. In addition to the large north polar layered deposits (NPLD) at Mars' north pole, smaller ice deposits are preserved in craters nearby. These outlying deposits were potentially formed by the same mechanisms that drive NPLD formation, or may represent more local mechanisms. Distinguishing between these possibilities would help elucidate the spatial homogeneity of Martian climate processes. Here, we analyzed SHARAD radar depth profiles from 34 locations across the NPLD and 5 locations within the Korolev crater ice deposit using Fourier transform analysis and dynamic time warping to quantitatively assess the similarity between the internal layered stratigraphy of the two deposits. We identify broad stratigraphic similarities between the Korolev deposit and the NPLD, suggesting they likely formed due to the same climate forcing mechanism, with local variability also observed across the NPLD. Plain Language Summary: Mars has two large ice caps at its poles, which combined contain a similar volume of ice to Greenland on Earth. Near these large ice caps are craters that are also filled with ice, which may or may not have formed due to the same mechanisms that formed the large neighboring ice cap. Ground penetrating radar observations of ice on Mars can allow us to see layers of ice and dust that are present throughout the interior of these deposits, and represent climate events that have taken place during the deposit's formation and evolution. We analyze radar observations from two deposits near Mars' north pole and quantitatively show that these deposits have a similar pattern of layering. These results could indicate that they have shared a similar climate history, therefore implying the importance of regional‐scale climate processes on Mars in addition to local processes for forming these ice deposits. Key Points: We use Fourier transform analysis and dynamic time warping to assess the similarities between two ice deposits near Mars' north poleWe identified a periodic signal with an average wavelength of ∼45 m in radar observations of the ice mound in Korolev crater and the NPLDWe identify similar broad climate forcing for both Korolev and NPLD ice, with local variability across the NPLD also observed [ABSTRACT FROM AUTHOR]

The evolution of charge structure involved in lightning discharge of a thunderstorm over the central Tibetan Plateau is investigated for the first time, based on the data from very high frequency interferometer, radar and sounding. During the developing‐mature stage, the TP thunderstorm exhibited a tripolar charge structure evolved from an initial inverted dipole. At the mature stage, a bottom‐heavy tripole charge structure is clearly presented, with a strong lower positive charge center (LPCC) at temperatures above −10°C, a middle negative charge region between −30°C and −15°C, and an upper positive charge region at T < −30°C. As the LPCC was depleted, the charge structure evolved into a normal tripole with a pocket LPCC. The merging between different convective cells resulted in the formation of two adjacent negative charge regions located directly and obliquely above the LPCC, and horizontally arranged different charge regions were simultaneously involved in the same lightning discharge. Plain Language Summary: Tibetan Plateau thunderstorms usually exhibit special convective structures. Using the data from the accurate lightning VHF interferometer, electric field mill, fast/slow antenna and C‐band radar, the evolution of the charge structure of thunderstorms and their influence on lightning discharges are investigated. Our observation for the first time revealed the charge structure evolution of the central‐TP thunderstorm which involved in the lightning discharge, exhibiting a bottom heavy tripole charge structure with a large LPCC in the mature stage evolved from an initial inverted dipole and the usual tripole in the dissipating stage of the thunderstorm. Under different magnitudes of the LPCC, different types of lightning discharges including ‐IC, +IC and ‐CG flashes were generated, indicating the crucial effects of LPCC on the lightning discharge types. Key Points: The charge structure of the TP thunderstorm evolves from an initial inverted dipole to a mature stage tripole with a strong LPCCHorizontally distributed negative charge zones from cell merger are simultaneously involved in the discharge of a single lightning flashDifferences in the relative magnitude of LPCC leads to various types of lightning discharges [ABSTRACT FROM AUTHOR]

Monitoring the generation and movement of equatorial plasma bubbles (EPBs) in a large longitude region is crucial important for better understanding their day‐to‐day variability. Using the newly developed Low lAtitude long Range Ionospheric raDar (LARID) at Dongfang (19.2°N, 108.8°E, dip lat. 13.8°N), China, an extremely long‐range experiment for observing EPB irregularities in a range of ±9,600 km to the radar site was first carried out. The results show that EPB irregularities with ranges up to 7,000 and 9,500 km were observed by the east and west beams of LARID, respectively. By incorporating simultaneous observations from GNSS receiver and ionosonde networks, it is demonstrated that the EPBs generated from post‐sunset to sunrise over a very wide longitude of ∼140°, from Pacific to Africa could be observed by LARID. The results, for the first time, demonstrate the possibility for tracing global EPBs in real time using a few low latitude over‐the‐horizon radars. Plain Language Summary: Equatorial plasma bubble (EPB), which can cause severe ionospheric scintillation, is an important space weather phenomenon. The occurrence of EPBs exhibits complex longitude variation characteristics. Due to the fact that most of the equatorial and low latitude region is covered by ocean, it is challenging to monitor the generation and movement of global EPBs. Recently, an over‐the‐horizon (OTH) radar at low latitude, that is, the LARID, has been built for observing EPB irregularities. However, it is not clear that how far an OTH radar at low latitude can observe irregularities. This would be very important in the design of a low latitude OTH radar network for tracing global EPB irregularities. To address this issue, an extremely long‐range experiment covering a wide longitude of about 180° was performed for the first time with LARID. The successful observation of EPB irregularities from Pacific to Africa sectors demonstrates the possibility of monitoring the complex longitudinal variations of EPBs by an OTH radar, even during geomagnetic storms. The results provide meaningful insight for building a low latitude OTH radar network in future, that consists of three to four OTH radars could have the capability to obtain global EPBs in real time. Key Points: First extremely long‐range experiment for observing equatorial plasma bubbles over a large longitude was conductedEquatorial plasma bubbles with ranges as far as 9,500 km were successfully observed by an over‐the‐horizon radarThe results demonstrate the capability for tracing global equatorial plasma bubbles using a few low latitude over‐the‐horizon radars [ABSTRACT FROM AUTHOR]

To address low detection accuracy and speed due to the multisolvability of the ground‐penetrating radar signal, we proposed a novel centralized feature pyramid‐YOLOv6l–based model to enhance detection precision and speed in road damage and pipeline detection. The centralized feature pyramid was used to obtain rich intra‐layer features and improve the network performance. Our proposed model achieves higher accuracy compared with the existing detection models. We also built two new evaluating indexes, relative average precision and relative mean average precision, to fully evaluate the detection accuracy. To verify the applicability of our model, we conducted a road field detection experiment on a ground‐penetrating radar dataset we collected and found that the proposed model had good performance in increasing detection precision, achieving the highest mean average precision compared with YOLOv7, YOLOv5 and YOLOx models, with relative mean average precision and frame rate per second at 16.38% and 30.5%, respectively. The detection information for the road damage and pipeline were used to conduct three‐dimensional imaging. Our model is suitable for object detection in ground‐penetrating radar images, thereby providing technical support for road damage and underground pipeline detection. [ABSTRACT FROM AUTHOR]

When I fiddle with my hair, or adjust my posture, it is plausible that these activities fall well below my cognitive radar. Some have argued that these are examples of ‘sub‐intentional actions’, actions which are not intentional under any description at all. If true, they are direct counterexamples to the dominant view on which the difference between actions and other events is their intentionality. In this paper, I argue that the case for sub‐intentional actions fails. Firstly, I show that the main argument for the sub‐intentionality of these actions has a structural fault. Secondly, I argue that two apparently natural ways to remedy this fail. Thirdly, I argue that one of the main arguments for thinking of the phenomena as actions undermines thinking of them as sub‐intentional. Finally, I argue that a natural defensive move for the defender of sub‐intentional actions actually undermines the theoretical significance of the view. Ultimately, my aim is to show that although the case for sub‐intentional actions seemed both simple and compelling, it is in fact deeply troubled. [ABSTRACT FROM AUTHOR]

More often, in the mathematical literature, the injectivity of the spherical Radon transform (SRT) for compactly supported functions is considered. In this article, an additional condition, for the reconstruction of an unknown function f∈C(R2)$f\in C(\mathbf {R}^2)$ (the support can be noncompact) using the circular Radon transform (CRT) over circles centered on a smooth simple curve is found. It is proved that this problem is equivalent to the injectivity of a so‐called two‐data CRT over circles centered on a smooth curve (can be a segment). Also, we present an inversion formula of the transform that uses the local data of the circular integrals to reconstruct the unknown function. Such inversions are the mathematical base of modern modalities of imaging, such as thermo‐ and photoacoustic tomography and radar imaging, and have theoretical significance. [ABSTRACT FROM AUTHOR]

Precise radar pulse detection is the premise of electronic support measures. A constant false alarm rate (CFAR) detection algorithm based on difference of box (DOB) filter is proposed to realise low‐complexity and environment‐adaptive radar pulse detection, and the principle behind the proposed algorithm is revealed. Specifically, the DOB filter is adopted to extract the rising edges and falling edges of radar pulses, and the signal variation law of probability density functions (PDFs) during the process of DOB filter are first theoretically analysed. Based on the derived PDFs, dynamic detection threshold and fixed threshold factor for the proposed CFAR algorithm based on DOB filter are deduced to detect the presence of radar pulses. Furthermore, the closed‐form expression of the detection probability is derived. Simulations and on‐board field programmable gate arrays implementation verify the superiority of the proposed CFAR algorithm based on DOB filter. Simulation results show that the proposed algorithm performs well in detecting various types of pulse signals, the detection probability ≥99% on condition that the signal‐to‐noise ratio ≥3 dB and false alarm probability = 10−8. Moreover, the proposed CFAR algorithm based on DOB filter can deal with both singular pulses and pulse on pulse signals. [ABSTRACT FROM AUTHOR]

Traditional radar systems use fixed patterns and constant electromagnetic wave transmission to illuminate targets, but they often do not effectively use prior information about targets and consume significant radar resources. Cognitive radar has emerged as a way to improve resource efficiency and address these shortcomings. A joint waveform design and resource allocation strategy for cognitive radar that incorporates target situational awareness is proposed. This method integrates the interacting multiple model algorithm and the Unscented Kalman Particle Filter to achieve target situation awareness as prior knowledge. By combining the target attitude and the frequency response function of the target radar cross section at different time points in the prior knowledge, a joint beam control and power allocation strategy is formulated and transformed into an optimization problem. In addition, a cognitive pulse‐to‐pulse frequency agile waveform design method is proposed to support multiple target tracking under complex motion models. Simulation experiments demonstrate the effectiveness of this approach in obtaining accurate target situation information, achieving beam control, and optimizing power allocation. The designed waveforms can enhance radar target detection performance and improve low probability of intercept characteristics by adjusting the pulse repetition interval. This method has significant technical value. [ABSTRACT FROM AUTHOR]

In tracking scenarios involving groups with dense targets, achieving effective data association is challenging due to mutual occlusion and interference among targets. The complexity of the tracking problem is further exacerbated in low‐observable environments by the increase in false alarm rates. The track‐before‐detect (TBD) is an advanced technology for detecting and tracking low‐observable targets, effectively mitigating data association problems by integrating multi‐frame echo data. However, the existing multi‐target TBD algorithms typically assume that the targets are spatially separated and are not suitable for scenarios involving group targets. A group target maximum‐likelihood probabilistic data association (GT‐ML‐PDA) algorithm, based on the concept of TBD, is proposed to track group targets effectively in low‐observable environments. The proposed algorithm divides group target tracking into two stages: group centre trajectory estimation and individual target trajectory estimation. To enhance the performance of the proposed algorithm, two strategies are suggested: modifying the equivalent measurements and extracting independent measurement sets for individual targets. Simulation results demonstrate that the proposed algorithm is capable of effectively tracking numerous individual targets within a group, even in the presence of heavy clutter. [ABSTRACT FROM AUTHOR]

Radar High‐Resolution Range Profile (HRRP) has great potential for target recognition because it can provide target structural information. Existing work commonly applies deep learning to extract deep features from HRRPs and achieve impressive recognition performance. However, most approaches are unable to distinguish between the target and non‐target regions in the feature extraction process and do not fully consider the impact of background noise, which is harmful to recognition, especially at low signal‐to‐noise ratios (SNR). To tackle these problems, the authors propose a radar HRRP target recognition framework termed Adaptive Soft Threshold Transformer (ASTT), which is composed of a patch embedding (PE) layer, ASTT blocks, and Discrete Wavelet Patch Merging (DWPM) layers. Given the limited semantic information of individual range cells, the PE layer integrates nearby isolated range cells into semantically explicit target structure patches. Thanks to its convolutional layer and attention mechanism, the ASTT blocks assign a weight to each patch to locate the target areas in the HRRP while capturing local features and constructing sequence correlations. Moreover, the ASTT block efficiently filters noise features in combination with a soft threshold function to further enhance the recognition performance at low SNR, where the threshold is adaptively determined. Utilising the reversibility of the discrete wavelet transform, the DWPM layer efficiently eliminates the loss of valuable information during the pooling process. Experiments based on simulated and measured datasets show that the proposed method has excellent target recognition performance, noise robustness, and small‐scale range shift robustness. [ABSTRACT FROM AUTHOR]

We propose a 10‐GHz 2 × 2 phased‐array radio frequency (RF) receiver with an 8‐bit linear phase and 15‐dB gain control range using 65‐nm complementary metal–oxide–semiconductor technology. An 8 × 8 phased‐array receiver module is implemented using 16 2 × 2 RF phased‐array integrated circuits. The receiver chip has four single‐to‐differential low‐noise amplifier and gain‐controlled phase‐shifter (GCPS) channels, four channel combiners, and a 50‐Ω driver. Using a novel complementary bias technique in a phase‐shifting core circuit and an equivalent resistance‐controlled resistor–inductor–capacitor load, the GCPS based on vector–sum structure increases the phase resolution with weighting‐factor controllability, enabling the vector–sum phase‐shifting circuit to require a low current and small area due to its small 1.2‐V supply. The 2 × 2 phased‐array RF receiver chip has a power gain of 21 dB per channel and a 5.7‐dB maximum single‐channel noise‐figure gain. The chip shows 8‐bit phase states with a 2.39° root mean‐square (RMS) phase error and a 0.4‐dB RMS gain error with a 15‐dB gain control range for a 2.5° RMS phase error over the 10 to10.5‐GHz band. [ABSTRACT FROM AUTHOR]

The unusual stripe‐like scattered echoes were observed by the Hainan Coherent Scatter Phased Array Radar (HCOPAR) in the nigh of 9 Sep. 2017. There were parallel stripes with the interval of ∼33 min appearing from 12:57 to 17:50 UT. While the emergence of the scattered echoes, the Hainan Digisonde has observed the Spread‐F, and the Total Electron Content (TEC) maps recorded by the Global Navigation Satellite System (GNSS) in China show that there was no Equatorial Plasma Bubble (EPB), but the Medium‐Scale Traveling Ionospheric Disturbance (MSTID) traveled southwestward. The spatial and temporal distributions of the stripe‐like echoes and the MSTID show great consistency, indicating that the F‐region Field‐Aligned Irregularities were generated in the wave peaks and troughs of the MSTID. The MSTID has decayed greatly while reaching the HCOPAR, and the echo pattern is determined by the wave features of the MSTID. Key Points: Unusual stripe‐like echoes scattered from nighttime F‐region Field‐Aligned Irregularities were observed at low‐latitudesThe stripe‐like echo pattern exhibits a good correlation with the Medium‐Scale Traveling Ionospheric Disturbance (MSTID) observed in the Total Electron Content mapsThe scattered echoes were generated in wave troughs and peaks of the MSTID, and the echo pattern is determined by the wave features [ABSTRACT FROM AUTHOR]

The spectacular visual displays from the aurora come from curtains of excited atoms and molecules, impacted by energetic charged particles. These particles are accelerated from great distances in Earth's magnetotail, causing them to precipitate into the ionosphere. Energetic particle precipitation is associated with currents that generate electric fields, and the end result is a dissipation of the hundreds of gigawatts to terrawatts of energy injected into Earth's atmosphere during geomagnetic storms. While much is known about how the aurora dissipates energy through Joule heating, little is known about how it does so via small‐scale plasma turbulence. Here we show the first set of combined radar and optical images that track the position of this turbulence, relative to particle precipitation, with high spatial precision. During two geomagnetic storms occurring in 2021, we unambiguously show that small‐scale turbulence (several meters) is preferentially created on the edges of auroral forms. We find that turbulence appears both poleward and equatorward of auroral forms, as well as being nestled between auroral forms in the north‐south direction. These measurements make it clear that small scale auroral plasma turbulence is an integral part of the electrical current system created by the aurora, in the sense that turbulent transport around auroral forms enhances ionospheric energy deposition through Joule heating while at the same time reducing the average strength of the electric field. Plain Language Summary: The aurora continuous to amaze the inhabitants and travelers of Earth's polar regions. Bright shifting folds of light extend down from the nightsky, appearing as green, red, or faint‐blue curtains. During geomagnetic storms the are particularly bright and dynamic, often visible in large parts of the inhabited globe. However, far from being simple displays of light, the aurora can wreak havoc on the thin gas of Earth's upper atmosphere. There, gigantic swirls of electric turbulence are excited in response to the energy that is being pumped into the atmosphere by the aurora. This plasma turbulence is detrimental to satellite communication, such as the principle operation of the GPS network, and future efforts are sorely needed to understand the when and how this turbulence appears. We present a series of photographical and radar‐based images of the aurora and its plasma turbulence, shedding light on the complex relationship between the two phenomena. The images and videos we present are accessible and interesting to a public readership. Key Points: Small‐scale auroral plasma turbulence is created preferably outside of but not far from optical auroral formsTurbulence appears both poleward and equatorward of auroral arcsStrong electric fields that trigger meter‐size E region turbulence are sometimes seen before the onset of optical aurora [ABSTRACT FROM AUTHOR]

The Atmospheric InfraRed Sounder (AIRS) aboard Aqua provides essential long‐term data on vertical cloud fraction, particularly valuable in the Arctic region. This study offers a comprehensive assessment of Arctic vertical cloud fraction derived from AIRS through a comparison with independent ground‐ and space‐based radar and lidar observations. In comparison to the measurements at the North Slope Alaska site, results reveal a significant underestimation of low‐level cloud cover by AIRS, especially for near‐surface clouds, while mid‐ and high‐level cloud fractions show better consistency. In comparison to the satellite‐based product from 3S‐GEOPROF‐COMB, the accuracy varies across different underlying surfaces (land vs. sea) and seasons. AIRS shows significant positive biases in mid‐level cloud fraction over sea surfaces with sea ice concentration below 15%, indicating potential limitations in the cloud retrieval algorithm in regions with large sea ice variations. The issue of low‐level clouds identification is primarily caused by the limited penetrating capability of infrared hyperspectral sensing and the accuracy of preceding surface and atmospheric state products, which diminish the accuracy of AIRS low‐level cloud fraction. Plain Language Summary: The Atmospheric InfraRed Sounder (AIRS) instrument on the Aqua satellite provides important information on vertical cloud fraction in the Arctic. This research compared the AIRS cloud cover data with observations from ground‐based and space‐based radar and lidar. Findings are that AIRS underestimates low‐level clouds, especially near the surface, but is more accurate for mid‐ and high‐level clouds. The accuracy also varies over land and sea surfaces, as well as throughout different seasons. In regions with significant sea ice variations, AIRS overestimates clouds at mid‐levels. The study suggests that the ability to accurately detect low‐level clouds from AIRS is limited by the capability of infrared hyperspectral sensing to penetrate the atmosphere. Key Points: Initial evaluation of AIRS vertical cloud fraction product over the Arctic is presented using ground‐ and space‐based radar‐lidar observationsAIRS underestimates low‐level clouds, especially near the surface, more accurately reflects mid‐ and high‐level cloud fractionsAIRS mid‐level cloud fraction demonstrates significant positive biases over regions with sea ice concentration below 15% [ABSTRACT FROM AUTHOR]

Subglacial lakes have been mapped across Antarctica with two methods, radio‐echo sounding (RES) and ice‐surface deformation. At sites where both are coincident, these methods typically provide conflicting interpretations about the ice‐bed interface. With a single exception, active subglacial lakes identified by surface deformation do not display the expected flat, bright, and specular bed reflection in RES data, characteristic of non‐active lakes. This observational conundrum suggests that our understanding of Antarctic subglacial hydrology, especially beneath important fast‐moving ice streams, remains incomplete. Here, we use an airborne RES campaign that surveyed a well‐characterized group of active subglacial lakes on lower Mercer and Whillans ice streams, West Antarctica, to explore inconsistency between the two observational techniques. We test hypotheses of increased scattering and attenuation due to the presence of an active subglacial lake system that could suppress reflected bed‐echo power for RES observations in these locations, finding that entrained water is most plausible. Plain Language Summary: The bottom of an ice sheet is insulated from cold air temperatures, often warm enough to melt and pond liquid water into lakes. These lakes beneath the ice sheet have been identified by two independent measurements, first with radar methods and second with changes in height of the ice surface (altimetry). Interestingly, the two methods rarely identify the same lakes: radar generally detects lakes in the ice‐sheet interior, whereas altimetry detects active lakes near the ice‐sheet margins that fill and drain within the time series of repeated measurements (∼years). In this study, we investigate a group of active subglacial lakes at which both radar and altimetry data sets are available. We demonstrate that the radar returns from active lake reflections are much dimmer than expected based on non‐active lake signatures and investigate the physical processes controlling those dim reflections. We argue that water moves into the ice when the lake fills or drains and that is the most plausible explanation for the observational discrepancy. Key Points: Active subglacial lakes, identified by surface deformation, do not create the expected bright and specular radar reflectionEntrained water in basal ice suppresses radar power by scattering and attenuation, and it also likely alters the basal ice mechanicsUnderstanding the radar expression of subglacial water on Earth provides context for investigations of subsurface water on planetary bodies [ABSTRACT FROM AUTHOR]

Estimates of radar attenuation in the shallow Martian subsurface are retrieved from RIMFAX soundings along the Perseverance rover traverse. Specifically, analyzed data is from the Hawksbill Gap area during the rover's first drives onto the Jezero Western Fan Front. The centroid frequency‐shift method is employed to quantify attenuation in terms of the constant‐Q approximation. Results are then compared with the amplitude decay method, which—in order to calculate attenuation—requires propagation velocities retrieved from radargram analysis. By verifying that results from two separate analyses are consistent, we ensure that quantified radar properties are well constrained. First estimate of constant‐Q is 78.8 ± 11.6. For a subsurface propagation velocity of 0.113 m/ns, that equals an attenuation of −2.1 ± 0.4 dB/m at the RIMFAX 675 MHz center frequency. Results are consistent with dry sedimentary rocks, and are distinguishable from the magmatic lithologies on Jezero Crater Floor. Plain Language Summary: This study presents first estimates of radar attenuation at the Jezero Western Fan Front. Measurements were made with the RIMFAX payload instrument on the Mars 2020 Perseverance rover mission, acquired along the rover drive path. Results indicate low signal losses in the subsurface that are consistent with dry sedimentary rocks, as observed on the surface by other payload instruments. Maximum imaging depths increase compared to imaging over magmatic lithologies on Jezero Crater Floor. By using separate methods of analysis (the centroid frequency‐shift method and the amplitude decay method), we reliably quantify attenuation and maximum penetration depths at the Western Fan Front, and observe differences to the Crater Floor lithologies. Key Points: The first estimate of radar attenuation at the Jezero Western Fan Front is on average −2.1 dB/mFor an average propagation velocity of 0.113 m/ns, returned power and time‐frequency analyses yield similar resultsRadar properties are consistent with dry sedimentary rocks and are distinguishable from the magmatic lithologies on Jezero Crater Floor [ABSTRACT FROM AUTHOR]

Summary Multiple‐input multiple‐output (MIMO) radar, employing multiple transmitters and receivers, enhances radar capabilities. It detects and tracks objects like aircraft and ships using radio waves. Compared with traditional phased‐array radar, MIMO systems offer greater flexibility, improving angular resolution and target detection. Researchers focus on direction of arrival (DoA) evaluation for closely spaced targets. Effective beamforming and accurate DoA estimation are crucial for MIMO radar performance. This study explores two methods: Capon beamforming with Dolph–Chebyshev windowing and the MUSIC algorithm with Eigenvalue thresholding. Tested under low signal‐to‐noise ratio (SNR) and fewer snapshots, these techniques notably reduce side lobes and enhance angular resolution, validated by experiments. Additionally, the suppression of side lobes significantly improves the clarity and accuracy of target detection, minimizing potential interference and false targets. This enhancement in side lobe suppression facilitates a more precise spatial differentiation between multiple targets, thus contributing to the overall effectiveness and reliability of MIMO radar systems. [ABSTRACT FROM AUTHOR]

To ensure the ship navigation safety, it is necessary to detect the targets in the background of sea clutter around the ship. The most commonly used target detection equipments for ship navigation are marine radar and automatic identification system (AIS) device. However, marine radar echoes are often mixed with multiple clutter, and weak targets are not always equipped with AIS device, neither provides AIS information with low accuracy, leading to difficulty with target detection. Moreover, existing marine monitoring systems are accustomed to using the traditional information fusion methods for target detection, and the accuracy of identifying the weak targets is relatively low. To make full use of radar echo and AIS information and improve the accuracy of target detection, a Marine radar monitoring Internet of Things system is proposed, in which marine radars work in both scanning and staring modes. By adopting image segmentation and deep learning methods, the proposed design can enable accurate perception of weak target detection based on plan‐position indicator (PPI) images. A case study based on the selected X‐band radar datasets shows that the proposed design can achieve high target identification accuracy. [ABSTRACT FROM AUTHOR]

In this letter, a novel algorithm is proposed to design symbol‐level waveform for dual‐functional radar‐communication (DFRC) systems with low range sidelobe. Different from current schemes design waveform at the block level, a phase response constraint is introduced at the symbol level to provide an additional degree of freedom to decrease the range sidelobe in the pulse compression procedure, which is highly desired in radar systems. In particular, the phase response at the target direction is constrained to be similar to the given reference phase, and the matching error between the designed beampattern and the desired one is minimized subject to the constant modulus constraint. Furthermore, to guarantee the quality of service for communication, constructive interference is exploited at the symbol level for each communication user. An alternating direction method of multipliers algorithm is also proposed to solve the resulting nonconvex optimization problem with tractable subproblems solved sufficiently by the manifold optimization and standard quadratic problem. Numerical simulation results demonstrate the performance of the proposed method. [ABSTRACT FROM AUTHOR]

An ensemble three‐dimensional ensemble‐variational (3DEnVar) data assimilation (En3DA) approach that directly assimilates radar reflectivity was developed based on the Weather Research and Forecasting model data assimilation system. This system adopts radar reflectivity as the control variable to avoid the need for a tangent linear and adjoint of the observation operator. Flow‐dependent covariance was introduced via ensemble forecasts updated by a group of 3DEnVar. The performance of the En3DA system was examined for two selected cases of high‐impact severe tornadic supercells over China. Results for both cases indicated that the structure of the storms in terms of intensity, coverage, and associated low‐level mesocyclones were analysed more accurately when using the En3DA approach than when adopting the 3DVar method. Hydrometeor analysis showed that En3DA provided a more physically reasonable increment of hydrometeors compared to 3DVar, especially for the graupel mixing ratio. Furthermore, the En3DA forecast was better than the 3DVar forecast throughout the forecast period for both studied cases. En3DA produced smaller errors in terms of intensity and location for supercell forecasts with respect to reflectivity and reflectivity swaths. Furthermore, the quantitative forecast skill of radar reflectivity was improved using En3DA. Errors in the wind, temperature, and water vapor forecast fields produced by En3DA were also reduced compared to those of 3DVar. Diagnostics revealed that En3DA predicted an enhanced low‐level cold pool and stronger outflows in the forward‐flank downdraft and the rear‐flank downdraft regions, which are important for tornadogenesis. [ABSTRACT FROM AUTHOR]

Climate change is altering the timing of seasonal events for many taxa.There is limited understanding of how northward/southward songbird migration follows or is limited by the latitudinal progression of seasonal transitions. Consistent environmental conditions that migrating birds encounter across latitudes likely represent or correlate with important resources or limiting factors for migration.We tested whether migratory passage—observed via radar—consistently tracked land surface variables and phenophases across latitudes in the US Central Flyway in both spring and fall.The daily temperatures, precipitation and vegetation greenness occurring on 10%, 50% and 90% cumulative passage dates changed substantially with latitude, indicating that most migrants experienced rapidly changing conditions as they headed north or south. Temperature did not limit the progression of migration in either season.Peak spring migration in the southern US occurred nearly 40 days after the spring green wave, the northward progression of vegetation growth, but nearly caught up to green‐up at 48° N. Spring migration phenology may have evolved to prioritize earlier arrival for breeding.Across all latitudes, peak fall migration coincided with the same land surface phenophase, an interval of 26 days prior to dormancy onset. Migrants may rely on phenological events in vegetation during fall stopovers.Considering that (a) migratory passage tracked fall land surface phenology across latitudes at a continental scale, (b) previous studies at local scales have demonstrated the importance of fruit during fall migratory stopover and (c) fruiting phenology in North America is occurring later over time while fall migration is advancing, the potential for mismatch between fall fruiting and bird migration phenology urgently needs further investigation. [ABSTRACT FROM AUTHOR]

To enhance the capability of identifying unknown emitters in open spaces, an open‐multiscale attention kernel (MSAK)‐convolutional neural network‐long short‐term memory (CNN‐LSTM) structure is proposed. To this end, first, a MSAK module and CNN‐LSTM structure are introduced, and then, the depth and complexity of the feature extraction network are improved to enhance its representation capability. To classify unknown emitters accurately, the MSAK‐CNN‐LSTM model is improved to obtain an open‐MSAK‐CNN‐LSTM model with open‐set recognition capability. Additionally, the two preprocessing procedures are summarised, and their strengths and weaknesses are compared. Experimental results show that the proposed open‐MSAK‐CNN‐LSTM model achieves satisfactory accuracy in identifying unknown emitters in open space. In addition, it has significant advantages in low signal‐to‐noise ratio (SNR) scenarios. [ABSTRACT FROM AUTHOR]

The application of the hybrid extended Kalman filter (HEKF), hybrid unscented Kalman filter (HUKF), hybrid particle filter (HPF), and hybrid extended Kalman particle filter (HEKPF) is discussed for hybrid non‐linear filter problems, when prediction equations are continuous‐time and the update equations are discrete‐time, and also the discrete extended Kalman filter (DEKF), discrete unscented Kalman filter (DUKF), discrete particle filter (DPF), and discrete extended Kalman particle filter (DEKPF) for discrete‐time non‐linear filter problems, when prediction equations and update equations are discrete‐time. In order to assess the performance of the filters, the authors consider the non‐linear dynamics for a re‐entry vehicle. The filters are used in two hybrid and discrete states to estimate the position, velocity, and drag parameter associated with the re‐entry vehicle. Theoretical topics concerning estimating the drag parameter of a vehicle in re‐entry phase have been dealt with. Drag parameter estimation is carried out using a combination of hybrid filters and discrete filters as an effective estimator and fixed value, forgetting factor, and Robbins‐Monro stochastic approximation methods as the noise covariance matrix adjuster of the parameter. [ABSTRACT FROM AUTHOR]

Modern radar systems often face various interference signals in complex and rapidly changing electronic environments. The task of suppressing this interference in the radar echo signal to extract vital information is challenging. A radar interference suppression method is proposed based on a generative adversarial network (GAN). This method effectively recovers the target signal from the echo signal, which contains interference and noise, by leveraging the powerful fitting ability of GAN. Specifically, this method was tested using coherent suppression interference, smart noise interference, and noise frequency modulation suppression interference. We compared the proposed GAN method with recurrent neural network, short‐time Fourier transform time‐varying filtering, short‐time fractional Fourier transform time‐varying filtering algorithms and RNN approach. The results show that the interference suppression algorithm based on GAN is superior to the other three algorithms. [ABSTRACT FROM AUTHOR]

Beamforming is an effective way of resolving target direction and anti‐jamming in short wave (SW) radar systems. In conventional beamforming (CBF) at a certain frequency, to get high resolution, the array aperture should be increased, and this is often not allowed in practical applications. A new narrow beam forming (NBF) method for beam sharpening based on the generalised oblique projection (GOP) filter with a flexible parameter is proposed. This method uses a GOP filter bank to form deep nulls in the undesired azimuth range on the pattern and utilises the logic product process to synthesise the GOP filters' outputs and thus obtains a narrow beam. Compared to traditional beamforming methods, the result of NBF has the characteristics of narrower beam width and bigger side lobe suppression ratio (SLSR). Especially, a narrower beam can be obtained in the case of a small array aperture, which is valuable for practical applications. Experimental results of the range‐Doppler spectrum of short wave radar show that this narrow beam forming method can achieve super resolution of targets within a wide beam and greatly suppress clutter. Therefore, NBF can improve the azimuth resolution and achieve interference suppression in a conventional beam. [ABSTRACT FROM AUTHOR]

Forward‐looking radar imaging is a top priority due to a variety of applications. An airborne forward‐looking radar imaging approach via a modified propagator method (MPM) based on the planar phased array is proposed. It can obtain a better focusing effect without range migration correction. Through the MPM algorithm, the azimuth resolution can be enhanced greatly. Compared with the conventional synthetic aperture radar imaging algorithm, the left‐right ambiguity process can be avoided by generating two‐dimensional spatial spectra. Furthermore, the imaging results of different numbers of elements are given to provide an assessment of the imaging performance. Additionally, the authors proposed to apply the scanning planar phased array configuration to airborne forward‐looking two‐dimensional imaging for the first time. The validity of the method is proven by experiments. The image is more focused. Furthermore, the results of the experiments verify that the proposed method is fit for high‐speed situation and aircraft height variation condition. [ABSTRACT FROM AUTHOR]

Radar systems are a topic of great interest, especially due to their extensive range of applications and ability to operate in all weather conditions. Modern radars have high requirements such as its resolution, accuracy and robustness, depending on the application. Noise Radar Technology (NRT) has the upper hand when compared to conventional radar technology in several characteristics. Its robustness to jamming, low Mutual Interference and low probability of intercept are good examples of these advantages. However, its signal processing is more complex than that associated to a conventional radar. Artificial Intelligence (AI)‐based signal processing is getting increasing attention from the research community. However, there is yet not much research on these methods for noise radar signal processing. The aim of the authors is to provide general information regarding the research performed on radar systems using AI and draw conclusions about the future of AI in noise radar. The authors introduce the use of AI‐based algorithms for NRT and provide results for its use. [ABSTRACT FROM AUTHOR]

Robustness against Electronic Warfare/Electronic Defence attacks represents an important advantage of Noise Radar Technology (NRT). An evaluation of the related Low Probability of Detection (LPD) and of Intercept (LPI) is presented for Continuous Emission Noise Radar (CE‐NR) waveforms with different operational parameters, that is, "tailored", and with various "degrees of randomness". In this frame, three different noise radar waveforms, a phase Noise (APCN) and two "tailored" noise waveforms (FMeth and COSPAR), are compared by time–frequency analysis. Using a correlator (i.e. a two antennas) receiver, assuming a complete knowledge of the band (B) and duration (T) of the coherent emission of these waveforms, it will be shown that the LPD features of a CE‐NR do not significantly differ from those of any CE radar transmitting deterministic waveforms. However, in real operations, B and T are unknown; hence, assuming an instantaneous bandwidth estimation will show that the duration T can be estimated only for some specific "tailored" waveforms (of course, not to be operationally used). The effect of "tailoring" is analysed with prospects for future work. Finally, some limitations in the classification of these radar signals are analysed. [ABSTRACT FROM AUTHOR]

A novel method is proposed for rail fastener detection based on millimetre‐wave (mmWave) radar, mmWave radar fastener counter (MMW‐FC), which can accurately detect and record the fasteners in real‐time as the train traverses its route. Under circumstances where GNSS signals remain unavailable for prolonged durations, precise train localisation can be accomplished by correlating the number of fasteners derived from this method with the corresponding track map. Initially, MMW‐FC utilises fast Fourier transform and adaptive beamforming to focus the energy reflected from fasteners. Subsequently, it applies an adaptive template‐matching algorithm to detect each fastener. Furthermore, by leveraging known fastener spacing and the average time for trains to pass adjacent fasteners, the Kalman filter can execute precise speed tracking, used as a speed reference when adjusting the matching template adaptively. The experimental results indicate that the proposed method can precisely count the fasteners the train encounters in diverse road and speed conditions. The fastener counter maintains the Counting Error less than 0.067%, the speed error stays below 1.8 km/h, and the maximum values of the mean absolute error and root mean square error for speed are 0.7337 and 0.9584 km/h, respectively. [ABSTRACT FROM AUTHOR]

The utilisation of continuous random waveforms for radar, that is, noise radar, has been extensively studied as a candidate for low probability of intercept operation. However, compared with the more traditional pulse‐Doppler radar, noise radar systems are significantly more complicated to implement, which is likely why few systems exist. If noise radar systems are to see the light of day, system design, implementation, limitations etc., must be investigated. Therefore, the authors examine and detail the implementation of a real‐time noise radar system on a field programmable gate array. The system is capable of operating with 100% duty cycle, 200 MHz bandwidth, and 268 ms integration time while processing a range of about 8.5 km. Additionally, the system can perform real‐time moving target compensation to reduce cell migration. System performance is primarily limited by the memory bandwidth of the off‐chip dynamic random access memory. [ABSTRACT FROM AUTHOR]

Over 9 years of hourly surface current data from high‐frequency radar (HFR) off the US West Coast are analyzed using a Bayesian least‐squares fit for tidal components. The spatial resolution and geographic extent of HFR data allow us to assess the spatial structure of the non‐phase‐locked component of the tide. In the frequency domain, the record length and sampling rate allow resolution of discrete tidal lines corresponding to well‐known constituents and the near‐tidal broadband elevated continuum resulting from amplitude and phase modulation of the tides, known as cusps. The FES2014 tide model is used to remove the barotropic component of tidal surface currents in order to evaluate its contribution to the phase‐locked variance and spatial structure. The mean time scale of modulation is 243 days for the M2 constituent and 181 days for S2, with overlap in their range of values. These constituents' modulated amplitudes are significantly correlated in several regions, suggesting shared forcing mechanisms. Within the frequency band M2 ± 5 cycles per year, an average of 48% of energy is not at the phase‐locked frequency. When we remove the barotropic model, this increases to 64%. In both cases there is substantial regional variability. This indicates that a large fraction of tidal energy is not easily predicted (e.g., for satellite altimeter applications). The spatial autocorrelation of the non‐phase‐locked variance fraction drops to zero over a distance of 150 km, a scale that is comparable to the swath width of the Surface Water and Ocean Topography altimeter. Plain Language Summary: Tides in the ocean encompass both the highly predictable daily changes in sea level seen from the shore as well as a less predictable component that changes over time depending on seasonal conditions and wind. Tidal signals are detectable at the ocean surface, for example, via satellite or land‐based radar antenna. The time‐evolving tide signals interact with other processes in the ocean, like currents, and can become harder to predict and describe. Many studies have examined this aspect of tides. In this work, we use land‐based radar observations of ocean currents off the US West Coast to examine this process with high detail, using mathematical techniques to separate the tides from everything else and then evaluating how much the tide has been altered by other processes. This is useful because ocean‐observing satellites can observe a single part of the ocean only when the satellite passes overhead, approximately every 10–20 days, while the data we analyze are sampled hourly and thus more easily allow us to draw conclusions about how tides behave. Key Points: In the California Current System, High‐Frequency Radar resolves stationary and non‐stationary tidesBroadband cusps occur at tidal constituent frequencies, with M2 exhibiting annual modulationWe analyze the tidal modulation to assess physics governing non‐stationary tidal variability [ABSTRACT FROM AUTHOR]

The ground‐based, high‐frequency radars of the Super Dual Auroral Radar Network (SuperDARN) observe backscatter from ionospheric field‐aligned plasma irregularities and features on the Earth's surface out to ranges of several thousand kilometers via over‐the‐horizon propagation of transmitted radio waves. Interferometric techniques can be applied to the received signals at the primary and secondary antenna arrays to measure the vertical angle of arrival, or elevation angle, for more accurate geolocation of SuperDARN observations. However, the calibration of SuperDARN interferometer measurements remains challenging for several reasons, including a 2π phase ambiguity when solving for the time delay correction factor needed to account for differences in the electrical path lengths between signals received at the two antenna arrays. We present a new technique using multi‐frequency ionospheric and ground backscatter observations for the calibration of SuperDARN interferometer data, and demonstrate its application to both historical and recent data. Key Points: Calibration of Super Dual Auroral Radar Network (SuperDARN) interferometer angle of arrival data remains an outstanding challengeAnalysis of data at multiple frequencies can overcome the inherent 2π measurement ambiguity in the time delay correction factor (tdiff)Example applications are shown for historical and contemporary multi‐frequency SuperDARN observations [ABSTRACT FROM AUTHOR]

A THz radar, with its wide bandwidth, is capable of high‐resolution imaging down to the centimeter scale. In this study, a THz radar is applied to detect hydrometeors generated in a spray chamber. The observed backscattering signals show fluctuations at centimeter scales, indicating various hydrometeor distribution patterns along the radar beam. A co‐located High‐Speed Imaging (HSI) sensor is used to measure the Drop Size Distributions (DSD) in the spray chamber. The radar sampling beam is well aligned with the HSI probes, allowing an objective comparison between the remote sensing and in situ observations. In this study, the observed radar power is compared with the power estimated from the HSI measurements. Results show great consistency, with power difference smaller than 0.5 dB. This study demonstrates the feasibility and great potential of using a THz radar for ultra‐high‐resolution observations of clouds in a laboratory facility, and in the real atmosphere. Plain Language Summary: An improved understanding of how precipitation forms in clouds calls for new observational instruments and novel measurement strategies. Radars operating at ultra‐high frequency (a.k.a. THz radars) are known for their unprecedented resolution down to centimeter scale. Here, for the first time, we applied a THz radar to detect hydrometeors generated in a spray chamber. An additional in situ probe is utilized within the chamber to validate the THz radar observations. The radar beam is directed through the same volume that is sampled by the in situ probe, thus enabling an objective comparison between the in situ and remote sensing measurements. Different hydrometeor distributions are generated in the chamber, each being jointly observed by the radar and the in situ probes. Results show that the THz radar measurements agree well with the radar power calculated from the in situ observations. This unique experiment indicates promising scenarios of applying THz radar to cloud and precipitation studies in a laboratory facility and in the real atmosphere. Key Points: A novel experiment is conducted by applying a THz radar to detect hydrometeors generated in a spray chamberGood agreement between in situ and radar observations demonstrates the unique capability of THz radar for cloud and precipitation studiesImplications of applying THz radar to design novel observational strategies for solving fundamental gaps in cloud physics are demonstrated [ABSTRACT FROM AUTHOR]

Tornadoes, as highly destructive weather events, require accurate detection for effective decision‐making. Traditional radar‐based tornado detection algorithms (TDA) face challenges with limited tornado feature extraction capabilities, leading to high false alarm rates and low detection probabilities. This study introduces the Multi‐Task Identification Network (MTI‐Net), leveraging Doppler radar data to enhance tornado recognition. MTI‐Net integrates tornado detection and estimation tasks to acquire comprehensive spatial and locational information. As part of MTI‐Net, we introduce a novel backbone network of Multi‐Head Convolutional Block (MHCB), which incorporates Spatial and Channel Attention Units (SAU and CAU). SAU optimizes local tornado feature extraction, while CAU reduces false alarms by enhancing dependencies among input variables. Experiments demonstrate the superiority of MTI‐Net over TDA, with a decrease in false alarm rates from 0.94 to 0.46 and an increase in hit rates from 0.23 to 0.81, highlighting the effectiveness of MTI‐Net in handling small‐scale tornado events. Plain Language Summary: Tornadoes, highly destructive small‐scale weather phenomena, demand accurate detection for informed decision‐making. Although meteorological radars are commonly utilized for tornado identification, current methods often suffer from false alarms or missed detections due to radar noise. In this study, we introduce the multi‐task learning‐based identification network (MTI‐Net), which not only enables tornado detection but also estimates tornado counts within radar data. We integrate Convolutional Neural Networks (CNNs) with Transformer techniques to enhance the model's ability to capture tornado information. CNNs detect local details using filters, while Transformers manage global connections through attention mechanisms. A series of experiments demonstrate significant improvements in tornado detection with MTI‐Net compared to traditional methods. Key Points: A tornado dataset with detailed radar features was created over China from 2017 to 2023Multi‐task learning was designed to simultaneously infer tornado detection and tornado number estimationIntegration of spatial and channel attention units can better extract tornado features from radar data [ABSTRACT FROM AUTHOR]

Machine learning‐based approaches demonstrate a significant potential in radar quantitative precipitation estimation (QPE) applications. In contrast to conventional methods that depend on local raindrop size distributions, deep learning (DL) can establish an effective mapping from three‐dimensional radar observations to ground rain rates. However, the lack of transparency in DL models poses challenges toward understanding the underlying physical mechanisms that drive their outcomes. This study aims to develop a DL‐based QPE system and provide a physical explanation of radar precipitation estimation process. This research is designed by employing a deep neural network consisting of two modules. The first module is a quantitative precipitation estimation network that has the capability to learn precipitation patterns and spatial distribution from multidimensional polarimetric radar observations. The second module introduces a quantitative precipitation estimation shapley additive explanations method to quantify the influence of each radar observable on the model estimate across various precipitation intensities. Plain Language Summary: Ground radars can provide continuous spatial observations over large areas with high spatiotemporal resolutions, so they form the infrastructure for precipitation monitoring and observation in many countries. Recently, deep learning (DL) techniques have shown great potential for use in polarimetric radar‐based precipitation estimates. Nevertheless, the black‐box and turn‐key characteristics of DL models make it difficult for researchers to understand the model decision‐making process and cast doubt on the reliability of the model results. This study introduces a physically explainable polarization radar‐based quantitative precipitation estimation (QPE) system built on DL technology that can explain the causes of the precipitation estimates provided by deep learning models under different rainfall amounts. An experiment indicates that our model achieves better estimates than the conventional methods. Furthermore, the explainability methodology allows for visualization of the microphysical precipitation information. Being the initial attempt to apply explainability learning in the QPE domain, the explainability results may offer valuable guidance for rainfall estimation. Key Points: A polarimetric radar‐based rainfall estimation system is developed using deep neural networksThe deep learning‐based rainfall estimates generally outperform products derived from traditional parametric relationsThe proposed deep learning interpretation method can provide physical and statistical explanations of the model decision‐making process [ABSTRACT FROM AUTHOR]

We present the first continuous observations of three‐dimensional spatially resolved wind fields and atmospheric motions in the mesosphere and lower thermosphere in the mid‐latitudes of the Northern Hemisphere. Our observations were performed during a 19‐month campaign from January 2022 to July 2023 and exploited the composite data from the first multistatic meteor radar system in China and an adjacent monostatic meteor radar. To retrieve the atmospheric kinetic properties, we introduce an improved volume velocity processing method including coordinate transformations and non‐linear constraints to minimize errors. The vertical winds are estimated separately from the iteration of the horizontal divergence to avoid potential biases or contamination from the horizontal winds. The winds and air motions show annual/semiannual variation characteristics within certain altitudes, usually more variable around the equinoxes. The vertical winds are basically within the magnitude of 1 m/s and are upward as expected at the mesopause during the summer, which corresponds to the adiabatic cooling. Plain Language Summary: The mesosphere and lower thermosphere (MLT) is a coupling region between the upper and lower atmosphere and contains various dynamic and chemical processes. Meteor is a convenient and reliable tool for MLT mean horizontal wind observations. Multistatic meteor radars can investigate the more sophisticated dynamic properties of the MLT winds from different viewing angles. In this work, for the first time, we reported 3‐dimensional spatially resolved MLT winds and atmospheric motions in the mid‐latitudes of the Northern Hemisphere. To minimize errors in the retrieved winds, we proposed improvements to the volume velocity processing method by performing coordinate transformations and adding non‐linear constraints. The mean winds and air motions show annual/semiannual variations and are more variable near the equinoxes. Due to the small value of the vertical wind, we estimated it from the integration of the horizontal divergence and obtained a reasonable range of less than 1 m/s. The upwelling in the summer mesopause corresponds to the adiabatic cooling. Key Points: The first continuous observations of 3‐D spatially resolved winds and air motions in the Northern Hemisphere mid‐latitudes are reportedA newly developed volume velocity processing method including coordinate transformations and non‐linear constraints is introducedThe vertical wind is basically less than 1 m/s and is upward at the mesopause during summer, corresponding to the adiabatic cooling [ABSTRACT FROM AUTHOR]

Seabirds interact with fishing vessels to consume fishing discards and baits, sometimes resulting in incidental capture (bycatch) and the death of the bird, which has clear conservation implications. To understand seabird–fishery interactions at large spatiotemporal scales, researchers are increasing their use of simultaneous seabird and fishing vessel tracking. However, vessel tracking data can contain gaps due to technical problems, illicit manipulation, or lack of adoption of tracking monitoring systems. These gaps might lead to underestimating the fishing effort and bycatch rates and jeopardize the effectiveness of marine conservation. We deployed bird‐borne radar detector tags capable of recording radar signals from vessels. We placed tags on 88 shearwaters (Calonectris diomedea, Calonectris borealis, and Calonectris edwardsii) that forage in the northwestern Mediterranean Sea and the Canary Current Large Marine Ecosystem. We modeled vessel radar detections registered by the tags in relation to gridded automatic identification system (AIS) vessel tracking data to examine the spatiotemporal dynamics of seabird–vessel interactions and identify unreported fishing activity areas. Our models showed a moderate fit (area under the curve >0.7) to vessel tracking data, indicating a strong association of shearwaters to fishing vessels in major fishing grounds. Although in high‐marine‐traffic regions, radar detections were also driven by nonfishing vessels. The tags registered the presence of potential unregulated and unreported fishing vessels in West African waters, where merchant shipping is unusual but fishing activity is intense. Overall, bird‐borne radar detectors showed areas and periods when the association of seabirds with legal and illegal fishing vessels was high. Bird‐borne radar detectors could improve the focus of conservation efforts. [ABSTRACT FROM AUTHOR]

This article presents a dual‐band shared aperture antenna array designed for ASAR applications. The antenna array comprises eight elements for Chebyshev array configurations in both X/Ku‐bands. The proposed array achieves a scanning angle of ±25° by employing an interelement spacing of 0.7 λ. The layout mitigates mutual coupling effects and provides good isolation performance between the X‐ and Ku‐band antenna arrays across all synthesis techniques. Adopting the open, short, and load antenna array achieves different side lobe level (SLL) performances, >−25 dB. The isolation between bands and between the three conditions is quantified as follows: S16 = S61 = −68 dB, S15 = S51 = −55 dB, S12 = S21 = −46 dB, S43 = S34 = −49 dB, and S56 = S65 = −43 dB. The SLL values for each synthesis technique in the X/Ku‐band are as follows: Chebyshev simulated and measured results for open‐ended (X/Ku‐band: −26/−24 dB/−27/−26.8 dB). Furthermore, the antenna array achieves maximum realized gains in different positions (0°, 5°, 10°, 15°, 20°, 25°) in the X/Ku‐band. The gains for each synthesis technique are as follows: Chebyshev (The measured gain of this X/Ku‐band is high around 16.2/16.5 dBi (open‐ended), 13.1/14.2 dBi (short‐ended), and 15.3/15.2 dBi (load‐ended). The antenna array exhibits a comparatively wide impedance bandwidth Chebyshev (X/Ku‐band: 100/230 MHz). [ABSTRACT FROM AUTHOR]

Background: Wire‐guided localization has been the mainstay of localization techniques for non‐palpable breast and axillary lesions prior to excision. Evidence is still growing for relatively newer localization technologies. This study evaluated the efficacy of the wireless localization technology, SCOUT®, for both breast and axillary surgery. Methods: Data were extracted from a prospective database (2021–2023) of consecutive patients undergoing wide local excision, excisional biopsy, targeted axillary dissection, or axillary lymph node dissection with SCOUT at a high‐volume tertiary centre. Rates of successful reflector placement, intraoperative lesion localization, and reflector retrieval were evaluated. A survey of surgeon‐reported ease of lesion localization and reflector retrieval was also evaluated. Clinical trial registration: ACTRN386751. Results: One‐hundred‐ninety‐five reflectors were deployed in 172 patients. Median interval between deployment and surgery was 3 days (range 1–20) and mean distance from reflector to lesion was 3.2 mm (standard deviation, SD 3.1). Rate of successful localization and reflector retrieval was 100% for both breast and axillary procedures. Mean operating time was 65.8 min (SD 33). None of the reflectors migrated. No reflector deployment or localization‐related complications occurred. Ninety‐eight percent of surgeons were satisfied with ease of localization for the first half of cases. Conclusion: SCOUT is an accurate and reliable method to localize and excise both breast and axillary lesions, and it may overcome some of the limitations of wire‐guided localization. [ABSTRACT FROM AUTHOR]

The frequent occurrence of severe convective weather has certain adverse effects on the smart agriculture industry. To enhance the prediction of severe convective weather, the inversion model effectively fills radar reflectivity data gaps by leveraging geostationary satellite data, offering more comprehensive and accurate support for meteorological information in smart agriculture systems. Nevertheless, collaborative cross‐regional inversion driven by dispersed radar data faces challenges in efficiency, privacy, and model accuracy. To this end, we employ an U‐shaped residual network with an embedded light hybrid attention mechanism and utilize a federated averaging algorithm for efficient distributed training across multiple devices which could preserve the privacy of data from different locations, thereby improving inversion performance. In addition, to address the unbalanced nature of radar data, a weighted loss function is designed to enhance the model's sensitivity to high radar reflectivity. Experimental results demonstrate that the proposed model exhibits a certain level of improvement in evaluating radar reflectivity inversion performance across different thresholds compared to other models, thus substantiating the superiority of the proposed approach. [ABSTRACT FROM AUTHOR]

Placing wind turbines within large migration flyways, such as the North Sea basin, can contribute to the decline of vulnerable migratory bird populations by increasing mortality through collisions. Curtailment of wind turbines limited to short periods with intense migration can minimize these negative impacts, and near‐term bird migration forecasts can inform such decisions. Although near‐term forecasts are usually created with long‐term datasets, the pace of environmental alteration due to wind energy calls for the urgent development of conservation measures that rely on existing data, even when it does not have long temporal coverage.Here, we use 5 years of tracking bird radar data collected off the western Dutch coast, weather and phenological variables to develop seasonal near‐term forecasts of low‐altitude nocturnal bird migration over the southern North Sea.Overall, the models explained 71% of the variance and correctly predicted migration intensity above or below a threshold for intense hourly migration in more than 80% of hours in both seasons. However, the percentage of correctly predicted intense migration hours (top 5% of hours with the most intense migration) was low, likely due to the short‐term dataset and their rare occurrence. We, therefore, advise careful consideration of a curtailment threshold to achieve optimal results.Synthesis and applications: Near‐term forecasts of migration fluxes evaluated against measurements can be used to define curtailment thresholds for offshore wind energy. We show that to minimize collision risk for 50% of migrants, if predicted correctly, curtailments should be applied during 18 h in spring and 26 in autumn in the focal year of model assessments, resulting in an estimated annual wind energy loss of 0.12%. Drawing from the Dutch curtailment framework, which pioneered the 'international first' offshore curtailment, we argue that using forecasts developed from limited temporal datasets alongside expert insight and data‐driven policies can expedite conservation efforts in a rapidly changing world. This approach is particularly valuable in light of increasing interannual variability in weather conditions. [ABSTRACT FROM AUTHOR]

In electronic warfare, radar signal deinterleaving is a critical task. While many researchers have applied deep learning and utilised known radar classes to construct interleaved pulse sequences training sets for deinterleaving models, these models face challenges in distinguishing between known and unknown radar classes in open‐set scenarios. To address this challenge, the authors propose a novel model, the Reconstruction Bidirectional Recurrent Neural Network (RBi‐RNN). RBi‐RNN utilises input reconstruction and employs a joint training strategy incorporating cross‐entropy loss, reconstruction loss, and centre loss. These strategies aim to maximise inter‐class latent representation distances while minimising intra‐class disparities. By incorporating an open‐set recognition method based on extreme value theory, RBi‐RNN adapts to open‐set scenarios. Simulation results demonstrate the superiority of RBi‐RNN over conventional models in both closed‐set and open‐set scenarios. In open‐set scenarios, it successfully discriminates between known and unknown radar signals within interleaved pulse sequences, deinterleaving known radar classes with high stability. The authors lay the foundation for future unsupervised deinterleaving methods designed specifically for unknown radar pulses. [ABSTRACT FROM AUTHOR]

Two‐dimensional direction‐of‐arrival (DoA) estimation in azimuth and elevation via radar systems equipped with uniform rectangular arrays (URAs) will play an important role in various application areas—most distinctively in future urban air mobility settings with unmanned aerial vehicles. A key factor is the fast and reliable provision of target detections in terms of range and DoA for safe autonomous operation of the vehicle using on‐board antenna arrays with compact installation size. The authors present a technique for improving the performance of DoA estimation using compressive sensing in conjunction with multiple‐input multiple‐output arrays with electronically steered beams in the transmit direction. The simulation study investigates the impact of different design considerations on radar signal processing performance. An optimisation of a radar system using electronic beamsteering in the transmit domain is presented numerically. Based on the architecture of the URAs used, performance and detection accuracy can be improved. [ABSTRACT FROM AUTHOR]

X‐band marine radar observations and a hindcast simulation from a 3D hydrostatic model are used to provide an overview of Connecticut River (USA) ebb plume front expansion into the strong tidal crossflow of eastern Long Island Sound. The model performance is evaluated against in situ and remote sensing observations and demonstrates dominant control of the front by semidiurnal tides. The recurring frontal evolution is classified into three dynamical stages of arrest, propagation, and advection. A conceptual model that follows this progressing balance between outflow buoyancy and crossflow momentum qualitatively reproduces frontal evolution in both the radar observations and the hindcast. The majority of the residual, intertidal variability of front timing and geometry is explained by co‐varying tidal amplitude, freshwater discharge, and wind stress using a multi‐linear regression analysis of the radar observation record. Intrinsic front speeds in the modeled frontal propagation are compared with the analytical model of Benjamin (1968, https://doi.org/10.1017/s0022112068000133), with better agreement achieved after accounting for ambient near‐surface shear associated with wind forcing. Plain Language Summary: The fresh buoyant water that exits the Connecticut River mouth (USA) during each ebb tide expands as a plume, and floats above the denser waters of Long Island Sound. Currents in the Sound flow back and forth along the coast each tide, pushing the plume along the shore first to the east and then to the west. The location of the plume boundary (front) goes through a similar cycle almost every tide, initially being held stationary by eastward tidal currents, then expanding freely around slack tide, and subsequently being aided as it moves to the west by the ambient flow. Small changes to the arrival time and shape of the front are linked to changes in river discharge, tidal strength, and winds. Realistic simulations using a type of numerical model that aids coastal decision making are able to reproduce the tidal progression of front movement that was observed in 6 weeks of marine radar images of the water surface. Front movement in the numerical model also fits a simple analytical theory to a degree not previously seen on such a large scale, despite the complicating effects of wind. Key Points: Buoyant ebb plume front kinematics in a tidal cross‐flow are characterized by stages of arrest, propagation, and advectionWind, tide, and discharge variations explain modifications to the dominant semidiurnal control of the Connecticut River plume frontFront propagation in a hydrostatic numerical model reproduces both radar remote sensing observations and gravity current theory [ABSTRACT FROM AUTHOR]

This paper presents the first ever observations on aspect‐sensitive characteristics of 205 MHz stratosphere–troposphere (ST) radar located at a tropical station Cochin (10.04°N, 76.3°E) using volume scanning. The most significant and new observation is that the signal‐to‐noise ratio in zenith and off‐zenith beams are nearly equal in some height region, indicating the presence of isotropic turbulence. Signal strength decreases by 0.75 dB per degree from 0 to 10 degree off‐zenith, 0.9 dB per degree from 10 to 20 degree off‐zenith and 0.3 dB per degree beyond 20 degree off‐zenith. Different causative mechanisms are discussed on the basis of various estimated parameters associated with aspect sensitivity. Maximum aspect sensitivity is observed between 12 and 17 km, indicating the presence of dynamic instability arising due to strong wind shear and atmospheric stability. When both the square of wind shear and stability parameters are above 0.25 × 10−3 s−2, the scatterers become mostly isotropic. The study also shows a power difference in the symmetric beams as well as azimuth angle dependency. Analysis suggests that this asymmetry is due to the tilting of layers by the action of atmospheric gravity waves generated through Kelvin‐Helmholtz instability. The present configuration of radar can provide a better understanding of three‐dimensional structures of turbulence and instabilities. Plain Language Summary: Radar backscatter from the atmosphere depends directly on the turbulent scale sizes present and the probing frequency. When the backscatter echo strength decays with the radar viewing zenith angle, the signals are said to be aspect sensitive that is, dependent on the viewing angle. There can be few circumstances under which such characteristics are observed, all primarily being anisotropic scattering processes which are caused due to various processes in the atmosphere. Such aspect sensitivity must be quantified for realizing the accurate operation of a radar which would otherwise result in underestimation of winds and other parameters obtained from the radar. Here the aspect sensitivity characteristics of the 205 MHz stratosphere‐troposphere (ST) radar installed at Cochin (10.04°N, 76.33°E) are studied using a detailed experiment using various probing techniques during Indian Summer Monsoon season and the characteristics of the atmosphere during that period are probed to explain the aspect sensitivity. Key Points: First observations of aspect‐sensitivity characteristics at 205 MHz stratosphere–troposphere radarMechanisms for the formation of isotropic and anisotropic turbulenceModulation of aspect sensitivity by wind shear and atmospheric stability [ABSTRACT FROM AUTHOR]

Nowadays, modern radar systems increase their target detection capabilities by processing pulses coherently. On the other hand, digital radio frequency memory‐based modern jammers have the ability to work coherently and can deceive radars even with a very low effective radiated power. These jammers, which have the capability of storing the radar's pulse, can use the previous pulses that they have stored in their memory during the electronic deception, without waiting for the last pulse of the radar, in other words, before the new pulse is received. If the radar does not change its parameters from pulse to pulse, such smart jamming techniques applied in this way can be very effective. In this article, the authors propose to use a smart binary phase‐coding method for pulse compression radar as an electronic protection technique against repeater jamming. This approach further improves the target detection capability of modern radar systems, which use coherent integration in the receiver. The proposed method can provide high protection against digital radio frequency memory‐based repetitive range deception techniques without compromising the radar's target detection capability. In the simulations, the traditional approach in which the same code is used without changing from pulse‐to‐pulse, and the approach using code sets obtained by the smart binary phase‐coding method in intra‐pulse modulation are compared. The results show that the proposed method can significantly improve the isolation against deception jamming and the target detection capability simultaneously. [ABSTRACT FROM AUTHOR]

The Alps are a natural barrier for avian broad‐front migration in Central Europe. While most birds that approach the Alps are deflected and circumvent the mountains, some choose to make the crossing. Here, they are funnelled and channelled in valleys, leading to high bird densities. Many Alpine valleys are suitable locations for wind farms, potentially creating a conflict between wind energy production and bird conservation. Collisions can be reduced by temporarily shutting down wind turbines. This however requires timely coordination, either by locally monitoring migration intensity or by extrapolating and forecasting migratory fluxes from other sites. However, little is known about the timing and intensity of bird migration in valleys of the central Alps, especially during spring migration. This study presents a 2‐year quantification of avian migration across the Alps. We collected terrestrial radar data at three sites: two located in Alpine valleys and one in the lowland, close to the northern foothills of the Alps. We found high migration traffic rates (MTR) during both migration seasons in the Alpine valleys, with outstanding numbers of migrants during the spring season. The strong alignment of the flight directions with the main orientation of alpine valleys highlights the importance of valleys and the connected passes in channelling migratory fluxes through the Alps. However, extrapolating migration intensities and forecasting peak migration events for inner Alpine sites is difficult, likely due to how migratory patterns and activity are influenced by the complexity of the local topography and the associated dynamic wind and weather conditions. Instead, we call for year‐round on‐site monitoring of migration intensities and strategies tailored to the local context to reduce the risk of bird strikes at wind turbines in the Alps. [ABSTRACT FROM AUTHOR]