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• HF & VHF radars, making measurements of resident space objects, detect Doppler oscillations. • The Doppler oscillations are interpreted as waves propagating in the ionosphere. • Statistical analysis shows the waves have a frequency distribution in the 0.2–1 Hz range. • The waves are most likely observed during day with higher frequencies in weaker ionospheres. • The wave frequency and occurrence distributions suggest the most likely waves are EMIC waves. Radars performing observations of resident space objects (RSO) measure Doppler variations in wave events of several minutes duration, with frequencies in the 0.2–1 Hz range peaking near 0.5–0.7 Hz, consistent with variations in electron density induced by waves in the intervening ionosphere. The two mid-latitude radars used were a Very High Frequency (VHF) radar operating at 55 MHz, and a High Frequency (HF) radar operating at 30 MHz, both in southern Australia. The VHF radar wave observations exibited a peak in wave occurrence in the post-dawn sector (0600–1200 local solar time). The seasonal occurrence of the waves had a strong minimum during winter compared with the other seasons. Comparison between observations in 2018/19 (near solar minimum) and 2021/22 (mid-rise to cycle 25 peak) suggests wave occurrence is anti-correlated with sunspot number and hence with EUV and ionospheric strength. Generally the waves had higher frequencies during night than day, and low sunspot number than mid solar cycle, when there was a weaker ionosphere. Given the oscillation frequency of the wave events, the most likely geophysical phenomena that is consistent with the observations are electro-magnetic ion cyclotron (EMIC) plasma waves in the Pc1 (0.2–5 Hz) frequency range. No other candidate geophysical disturbance appears to fit the wave characteristics. The majority of geomagnetic field-guided transverse Pc1 EMICWs project from the outer magnetosphere down onto the polar ionosphere, where they can convert to compressional fast-mode waves propagating parallel to the Earths surface in the ionospheric F2 layer waveguide, both equatorwards to mid-latitudes and polewards. It is likely the majority of the Doppler oscillations in the Pc1 frequency range observed by the radars at mid-latitudes are these ducted compressional waves. However, sources of transverse EMICWs from the magnetosphere onto the mid-latitude ionosphere do exist, and these may cause some of the observed oscillations. The micro-physics of these compressional waves causing Doppler oscillations in radio observations is not inconsistent with the history of ionospheric Doppler measurements and theory, although the radar trans-ionospheric radio propagation and the observed waves being higher frequency than previous studies is different. If the observed Doppler oscillations are compressional EMICW in the ionospheric waveguide then several of the statistical results can be explained. The anti-correlation of the wave occurrence with sunspot number (and resultant ionospheric strength) can be attributed to lower ionospheric attenuation at the higher latitudes, between where geomagnetically field-guided transverse EMIC waves initially enter the high-latitude ionospheric waveguide from the magnetosphere above, and their observation at mid-latitudes. The observation of higher frequency waves during low sunspot number may also be explained by a source effect in the magnetosphere that preferentially selects the higher frequency field-guided transverse EMIC waves to propagate down to the ionosphere. Comparisons will be shown with results from ground and space based magnetometers of compressional waves in the waveguide, highlighting consistent results and areas where the measurement techniques differ. Theory suggests the radar Doppler measurements are far more sensitive to variations in in-situ ionospheric electron density than magnetic field variations. This agrees with existing literature which highlights the very strong contribution from the compressional component. Theory also suggests that the Doppler sensitivity of a radar to ionospheric electron density variations is frequency dependent, with lower frequencies being more sensitive. This is borne out by the measurements, with the HF radar being more sensitive than the VHF radar. [ABSTRACT FROM AUTHOR]

The objective of this paper is to analyze the performance of two possible architectures of tethered satellite systems, used as a platform for a distributed radar sounder. The first architecture consists in a cross-track oriented tethered satellite system, controlled and stabilized by exploiting the aerodynamic forces generated by the interaction with the rarefied atmosphere in Low Earth Orbit. The second architecture involves a tethered satellite system controlled through gyroscopic stabilization, obtained by spinning the system about an axis contained in the orbital plane. After a brief survey of radar sounding techniques, the methodology is introduced for describing the geometry of the systems and their characteristics, the performance of the two architectures are then compared with each other and with the current state of the art. By analyzing the modeled nominal behavior, it is shown that the two proposed architectures can achieve continuous or multiple observations, respectively, at maximum cross-track resolution, during one orbit, minimizing clutter noise. This is a considerable improvement of performance versus a formation flight architecture which can typically achieve only up to four observations per orbit. Finally, the advantages and disadvantages of each architecture are studied, and their possible mission scenarios are discussed. • A Tethered Satellite System is proposed, flying with tether in cross-track direction. • The tether tension is generated by aerodynamic lift forces on plates at its extrema. • Antenna elements distributed along the tether enable radar sounding applications. • Top radar sounding performances are achieved everywhere along the orbit. • An alternative gyroscopic tether system is studied for planets with no atmosphere. [ABSTRACT FROM AUTHOR]

This study focuses on the improvement of the tracking performance of space observation radar systems. Coherent radar systems usually provide an observation vector including four observables (range, range rate, azimuth, elevation) measured at a given epoch. Moreover, for some coherent radars, such as the TIRA system, it is possible to determine an additional parameter, the range rate, which is extracted from the collected complex amplitude. The tracking performance can be improved by increasing the observation parameter accuracy. The influence of each parameter on the overall tracking performance can be assessed by conducting a sensitivity analysis. The investigation shows that the best way to increase the accuracy of the state vector is by improving the angle estimates. The TIRA system is equipped with a tracking radar and an imaging radar. A powerful solution to improve the tracking performance is the realization of a multi-sensor data fusion between the two radars of the system. [ABSTRACT FROM AUTHOR]

Low-cost and high-efficiency electromagnetic wave absorption materials had extremely broad application prospects in the realms of military and civilian domains. A series of Ni-based PCS-derived adsorbents made from precursor infiltration pyrolysis at different pyrolysis temperatures were investigated in this research. The results showed that after being pyrolyzed at 1200 °C, the Ni-based PCS-derived adsorbent possessed the lowest reflection loss value of −59.52 dB, while it reached a peak effective absorption bandwidth of 2.84 GHz with 1000 °C treatment, of which the calculated electromagnetic absorption efficiency was meanwhile the best. Besides, the simulation results showed that the adsorbent after being pyrolyzed at 1000 °C could minimize the radar cross section of the target, of which the strongest radar cross section reduction value was 21.34 dB·m2, significantly enhancing its stealth performance. Therefore, the Ni-based PCS-derived adsorbent possessed great electromagnetic wave absorption performances under conditions of high-temperature pyrolysis, which provided a reference for future electromagnetic wave absorption material design. [ABSTRACT FROM AUTHOR]

Ensuring the safety and operational efficiency of hydraulic infrastructures is paramount, considering the widespread consequences that damages can inflict on people, communities, and the environment. To mitigate risks and prevent significant losses, continuous surveillance is vital. While some damages might appear minor, they can jeopardize the complete operational reliability of dams, leading to substantial economic losses, especially in energy production and related activities. The rapid growth in 20th-century infrastructure development globally has made security monitoring a necessity for numerous civil structures. Rigorous inspection programs, particularly for reservoir dams, are essential for safeguarding citizens and their properties. However, individually monitoring each dam is often impractical due to the associated costs and time constraints, potentially posing safety risks. Fortunately, satellite-based differential radar interferometry (DInSAR) offers an effective and cost-efficient remote sensing solution. Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) techniques, particularly utilizing Persistent Scatterers, have proven successful in monitoring various infrastructures, natural phenomena, and geological activities. MT-InSAR provides precise measurements without the need for fieldwork, utilizing historical SAR image archives dating back to the 1990s. Technological advancements, such as the Sentinel-1 C-band with a six-day revisit time until the end of 2021, have enhanced monitoring capabilities. Additionally, commercial radar images in the X-band and the development of multi-interferometric InSAR techniques have opened new avenues for monitoring. This study showcases the adaptation and application of MT-InSAR for monitoring dams and large ponds constructed with loose materials. By assessing vertical displacements and consolidation rates, the technique identifies potential issues, aiding in further field investigations. Case studies involving dams and large reservoirs in Andalusia illustrate the effectiveness of satellite radar interferometry in monitoring their structural stability from space as a routine practice. [ABSTRACT FROM AUTHOR]

A fully automated processing system for measuring long-term ground deformation time series and deformation rates frame-by-frame using the Differential Interferometric Synthetic Aperture Radar (DInSAR) processing technique was developed and tested. Among the several factors that affect DInSAR's precision, such as temporal decorrelation and atmospheric noise, it was observed that seasonal spatial-temporal variability in radar penetration depth is the greatest contributor to the loss of precision of the long-term deformation rate measurement. This spatial-temporal signal is described for a specific region in the northern US; however, it is widely observed in multiple regions. In these regions, a gradual penetration depth increase is observed in fall and winter, and an abrupt penetration depth decrease is observed in spring. The latter effect is likely caused by rapid melting of ice and snow that, at the same time, significantly reduces interferometric coherence. Within a specific geographic region, radar penetration depth spatially varies proportionally to the elevation due to an elevation-dependent temperature gradient, producing artifacts that correlate well with the topography. This signal does not extend to high-elevation regions (above ~2500 m) that do not experience seasonal thawing, which allows for distinguishing it from the topography-dependent atmospheric signals. Without accounting for the spatial-temporal variability in radar penetration depth, deformation time series in these areas can contain either an annual periodic signal with an amplitude of over 0.1 m or, if the abrupt penetration depth decrease produced by melting is not resolved due to lower coherence, an erroneous interannual trend. Spatial-temporal variability in radar penetration depth needs to be better understood and corrected to improve the precision of long-term deformation rate products, particularly in regions susceptible to seasonal freezing and thawing. [ABSTRACT FROM AUTHOR]

This paper focuses on the automated extraction of textural features from segmented Sentinel-1A Synthetic Aperture Radar (SAR) imagery, which was captured on 25th August 2017. Textural properties play a pivotal role in discerning regions of interest in satellite imagery, essential for precise classification in diverse applications, including remote sensing, medical image analysis, biometric analysis, and document image analysis. To achieve this, the Local Adaptive Threshold (LAT) technique was employed for segmenting the foreground and background areas of the pre-processed vertical transmit-vertical receive (VV) polarized Sentinel-1A SAR data. The approach relies on second-order statistics, specifically co-occurrence measures, which evaluate the relationships between pairs of pixels within their local neighbourhood's in the input image. Four fundamental second-order statistical measures, namely correlation, energy, homogeneity, and contrast, were computed using the Grey Level Co-occurrence Matrix (GLCM). The GLCM was generated by quantizing the foreground region of the segmented grey-scale image into different levels, including 8, 16, and 64 grey levels, considering two inter-pixel distances, d=1 and d=2, and adopting an omni-directional orientation (θ = 00, 450, 900, 1350).The results underscore the effectiveness of the GLCM-based approach in computing second-order statistical texture measures from the segmented SAR image. Notably, the findings highlight that quantizing the image to Ng=8 with d=1 and considering omni-directional statistical measures (θ = 00, 450, 900, 1350) significantly enhances performance. [ABSTRACT FROM AUTHOR]

The utilization of Synthetic Aperture Radar (SAR) images for ship recognition holds significant importance within the realm of maritime surveillance and security. SAR images are useful for ship detection and recognition because they can penetrate through clouds and capture detailed information about ships, such as their size, shape, and orientation. In the context of ship recognition using SAR images, the primary objective is to employ automated methods for the identification and categorization of ships present in SAR imagery. The detection of ships in SAR images is a significant research area, but it remains challenging due to speckle noise, land clutters, and low signal-to-noise ratio. Researchers have developed various approaches to overcome this challenge, such as adaptive filtering, speckle reduction, and segmentation techniques. Hence, a ship detection method is devised that combines the active contour method and the YOLO-v8 model using deep learning techniques. In the first step, the SAR images undergo pre-processing and normalization, and the model is trained with the backbone network. The YOLO-v8 model, renowned for its proficiency in object detection, is applied to delineate precise bounding boxes around ships within the images. The results obtained from experiments conducted on a variety of SAR images convincingly demonstrate that the suggested approach attains proficient ship target detection, striking a balance between accuracy and comprehensiveness. This approach represents a promising solution to enhance ship detection in challenging SAR scenarios. [ABSTRACT FROM AUTHOR]

This study presents a generalised characterisation of the surface circulation over the northern shelf of the Gulf of Cadiz, based on 4 years of high-resolution satellite altimetry data from Sentinel-3A and wind model data. The altimetry-based surface zonal currents, adjusted for bottom-drag and wind effects, are compared with a generic CMEMS product and validated against in-situ ADCP measurements. The proposed altimetry product demonstrates superior performance than the CMEMS product, accurately reflecting surface circulation direction compared to in-situ measurements (r = 0.77, RMSE = 0.10 m/s, bias = 0.01 m/s). The use of the bottom-drag and wind-corrected/uncorrected altimetry product for spatiotemporal analysis of the shelf circulation revealed the distinct contributions of wind-driven and geostrophic components in different basin sectors. The results show that over the western basin, positive (eastward) surface currents were predominantly driven by westerly winds, while only occasionally, westward flows coincided with easterly winds, suggesting a higher control of the geostrophic component over the westward flows. In contrast, over the eastern basin, both eastward and westward flows were found to be primarily driven by favourable winds. Additionally, the analysis of Absolute Dynamic Topography (ADT) values along the whole basin showed the presence of ADT gradients both along-shore and cross-shore over the shelf, contributing to geostrophic flows. Finally, the seasonal analysis showed that eastward circulation tends to dominate during the spring and summer months, related to the upwelling season in the Gulf of Cadiz and associated westerly winds. Westward flows prevail during the winter months, related to easterly winds and the rebalancing of the along-shore sea level gradient during relaxed upwelling conditions. The findings demonstrate a significant improvement in the use of satellite altimetry data to study complex oceanographic dynamics in coastal areas, where both spatial and temporal variability are high. Moreover, the similarity of our results to those obtained from in-situ systems supports the use of altimetry data and publicly available wind models to support oceanographic studies in remote or resource-limited areas. [ABSTRACT FROM AUTHOR]

Due to the high mobility and strong concealment characteristics of synthetic aperture radar (SAR) targets, the corresponding SAR datasets exhibit few-shot data properties, and there is a significant lack of research on few-shot target detection methods in the SAR domain. Furthermore, this study is subject to the following limitations: the scarcity of SAR data and significant sample variations make it difficult to control class centers using existing methods, and the learned models tend to be biased towards base classes while easily confusing novel classes with base classes. These limitations hinder the generalization of knowledge from base classes when detecting novel class targets. In this work, we propose a novel few-shot SAR target detection method based on Gaussian meta-feature balanced aggregation (GMFBA), which is based on meta-learning. Specifically, we first propose two novel feature aggregation methods with Gaussian metrics, namely Gaussian projection distribution metric (GPDM) and Gaussian kernel mean embedding metric (GKMEM). By estimating class distribution with variational autoencoders to replace traditional class prototypes, we sample from robust distributions and measure projection Wasserstein distance and Gaussian kernel mean embedding distance with prior distributions, obtaining the best robust support features under the optimal measurement results. Then, based on GPDM and GKMEM, we propose a novel balanced inter-class uncorrelated aggregation (BICUA) method, which extracts support features of each class according to the proportion of samples and aggregates them with query features in a balanced manner, promoting feature representation between different classes and ensuring no interference between features to significantly reduce confusion between base classes and novel classes. Specifically, GMFBA outperforms the state-of-the-art method G-FSOD significantly in all settings, achieving state-of-the-art performance. In contrast, the novel class detection performance of GMFBA has shown an average improvement of 8.56% on split1 and split2 of the SRSDD-v1.0 dataset, and an average improvement of 1.41% on split1 and split2 of the MSAR-1.0 dataset. The code is available at https://github.com/Caltech-Z/GMFBA. [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]

Weather radar calibration is a crucial factor to be considered for quantitative applications, such as QPE (Quantitative Precipitation Estimation), which is used as input for weather risks management. The present work proposes a novel approach to the end-to-end radar calibration method through the characterization of the radar weighting functions. These are Gaussian functions that model an additional attenuation factor to the radar received power. This approach, based on the inclusion these parameters, allow the obtainment of a calibrated equivalent reflectivity factor expression for a Doppler dual-polarization weather radar that operates in the X band. To calculate these parameters, a UAS (Unmanned Aircraft System) was implemented for suspending the calibration target with a well-defined cross-section and for measuring its inclination due to wind using an IMU (Inertial Measurement Unit). From its measurements, the position of the target can be estimated, which is essential to the characterization of the weighting functions. Their inclusion within the radar equation, alongside the implementation of the angular measurement system highlight the innovation to the traditional radar calibration methodology that does not contemplate them from the explored state-of-the-art. The reflectivity was compared with the measurements from a disdrometer for a moderate rain event. An average reflectivity difference of 0.75 dBZ and a percent bias of 3.3 % were obtained between the expected and estimated measurements when including these functions compared to the 1.51 dBZ and –62.7 % obtained when disregarding them. These experimental results point out that the proposed method can deliver superior accuracy in the reflectivity estimation. [ABSTRACT FROM AUTHOR]