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Rainbands are essential to tropical cyclones (TCs), significantly affecting TC structure and intensity change. High‐resolution synthetic aperture radar (SAR) imagery can capture the footprints of rainbands caused by rain‐induced sea surface roughness modification. Using 464 SAR TC images, we investigated the rainband‐occurrence probability of TCs under different hemispheres, local times (LTs), intensities, and ocean basins. Results show that the rainband‐occurrence probability is highest in the downshear‐left quadrant for Northern Hemisphere TCs (downshear‐right quadrant for Southern Hemisphere TCs). For Northern Hemisphere TCs, the rainband‐occurrence probability is overall higher in the early morning (LT), and the peak region of rainband‐occurrence probability appears farther from the TC center in the evening (LT). Compared with weak TCs, the rainband‐occurrence probability becomes higher for strong TCs in the Northern Hemisphere. Furthermore, TCs have a higher rainband‐occurrence probability in the Northwest Pacific than in the North Atlantic and Northeast Pacific. Plain Language Summary: Rainbands are a salient feature of tropical cyclones (TCs) and are closely related to TC structure and intensity change. Synthetic aperture radar (SAR) can capture the sea surface imprint of rainbands beneath clouds caused by rain‐induced sea surface roughness modification. Using 464 SAR TC images, we made 464 rainband‐annotated data. The data were mapped to grid nodes spaced at 0.027 times the radius of max winds in a coordinate system with the origin at the TC center and the y‐axis in the vertical wind shear direction. Then, the data were composited to estimate and further investigate the rainband‐occurrence probability of TCs under different hemispheres, local times (LTs), intensities, and ocean basins. Results show that the rainband‐occurrence probability is highest in the downshear‐left quadrant for Northern Hemisphere TCs (downshear‐right quadrant for Southern Hemisphere TCs). For Northern Hemisphere TCs, the rainband‐occurrence probability is overall higher in the early morning (LT), and the peak region of rainband‐occurrence probability appears farther from the TC center in the evening (LT). Compared with weak TCs, the rainband‐occurrence probability becomes higher for strong TCs in the Northern Hemisphere. Furthermore, TCs have a higher rainband‐occurrence probability in the Northwestern Pacific than in the North Atlantic and Northeast Pacific. Key Points: The sea surface imprint of tropical cyclone (TC) rainbands in many synthetic aperture radar images reveals their occurrence probabilityThe rainband‐occurrence probability is overall higher in the early morning than in the evening. The feature is more obvious in strong TCsThe peak region of the probability appears farther from the TC center in the evening than in the early morning [ABSTRACT FROM AUTHOR]

Background: Previously, there has been some work in the field of optical imaging on phase compensation by employing Legendre polynomials as an expansion of the phase function, and this seems to be an appealing unstudied area in the field of ultrasound imaging. Purpose: The paper is devoted to solving one of the problems of enhancing the authenticity of diagnostics data obtained in ultrasound visualization systems and presents a novel approach to aberration correction, which ensures a reliable eliminating of phase distortions. The novelty of the proposed approach consists in the use of the decomposition of the wave front by Legendre polynomials to approximate aberrations of the phase front of ultrasonic waves propagating through distorting layers. Methods: The phase aberrations are corrected using a single sector probe that captures echoes in synthetic aperture mode. The proposed method approximates the changes in the wave front by means of the Legendre polynomials. The performance was investigated by placing a 13‐mm‐wide ultrasonic probe with 64 elements operating at 2 MHz on the surface of a commercial quality control phantom ATS Model 539 through a distorting layer. The following metrics were measured: peak value, root mean square (RMS), full width at half maximum (FWHM), contrast‐to‐noise ratio (CNR). During the experiments, three different aberrators were used interchangeably as distorting layers, two of which were made of photopolymer resin with RMS values of 39 and 97 ns and a speed of sound close to that of a human temporal bone tissue, and the third was an ex vivo human temporal bone with the RMS value of 44 ns. To test the correction, three regions inside the phantom were examined. Two‐sided nonparametric Wilcoxon rank‐sum test was used for assessing the statistical significance. The significance level for this study was set at α ≤ 0.05. To counteract the problem of multiple comparisons, the p‐values were adjusted by the Holm–Bonferroni correction method. Results: The statistically significant results have demonstrated the possibility of increasing peak intensity value up to 3.08 times, reducing the RMS width and FWHM of the intensity angular distribution down to 60% and 82%, respectively, and increasing CNR up to 2.12 times by using the proposed phase distortion correction method, compared with the case without correction. The results show that the method can be used as an effective aberration correction technique for all tested regions inside the phantom and distorting layers. Its usage allowed correcting up to 97% of the aberrations caused by the ex vivo temporal bone model. Conclusion: The results show that the usage of the proposed method for aberration correction can successfully increase the intensity and reduce the angular width of the ultrasound wave scattered by the point targets inside the phantoms. The method works with different distorting layers and is capable of correcting phase aberrations in multiple sections of the sonogram. The limitation of the proposed method consists in the fact that it requires the use of aperture synthesis and access to raw radiofrequency data, which restricts its application in common scanners. [ABSTRACT FROM AUTHOR]

In image processing, image segmentation is the process of partitioning a digital image into multiple image segments. Among state‐of‐the‐art methods, Markov random fields can be used to model dependencies between pixels and achieve a segmentation by minimising an associated cost function. Currently, finding the optimal set of segments for a given image modelled as a Markov random fields appears to be NP‐hard. The authors aim to take advantage of the exponential scalability of quantum computing to speed up the segmentation of synthetic aperture radar images. For that purpose, the authors propose a hybrid quantum annealing classical optimisation expectation maximisation algorithm to obtain optimal sets of segments. After proposing suitable formulations, the authors discuss the performances and the scalability of authors' approach on the D‐Wave quantum computer. The authors also propose a short study of optimal computation parameters to enlighten the limits and potential of the adiabatic quantum computation to solve large instances of combinatorial optimisation problems. [ABSTRACT FROM AUTHOR]

Accurate and robust time delay estimation is crucial for synthetic aperture sonar (SAS) imaging. A two‐step time delay estimation method based on displaced phase centre antenna (DPCA) micronavigation has been widely applied in motion estimation and compensation of SASs. However, the existing methods for time delay estimation are not sufficiently robust, which reduces the performance of SAS motion estimation. Deep learning is currently one of the cutting‐edge techniques and has brought about a remarkable progress in the field of underwater acoustic signal processing. In this study, a deep learning‐based time delay estimation method is introduced to SAS motion estimation and compensation. The subband processing is first applied to obtain ambiguous time delays between adjacent pings from phases of SAS echoes. Then, a lightweight neural network is utilised to construct phase unwrapping. The model of the employed neural network is trained with simulation data and applied to real SAS data. The results of time delay estimation and motion compensation demonstrate that the proposed neural network‐based method has much better performance than the two‐step and joint‐subband methods. [ABSTRACT FROM AUTHOR]

Summary: The reconstruction of reflectivity profile of the synthetic aperture radar (SAR) is an important field of research. SAR tomography is an advanced 3D imaging technique for the spectrum estimation in the elevation direction for each azimuth resolution cell. This work presents the processing chain for the tomographic reconstruction from ALOS PALSAR data for an urban region. First, the data are preprocessed by removing the speckle noise followed by atmospheric phase screen and topographic correction. Then the SAR images are stacked together with one master image and the remaining slave images on the baseline value. After the images are coregistered, the interferogram is generated from the image to obtain the difference of the phase value. Then the proposed super resolution SAR (SRS) algorithm is attempted for TomoSAR processing, which combines the functionality of modern machine learning method like deep learning with parametric block‐based compressive sensing approach. Finally, a 3D image is reconstructed from the input data. Evaluation is carried out by comparing the results of the proposed method with other spectrum estimation methods such as nonlinear least square, Capon, and multisignal classification. The normal baseline of the interferometric fringes is about 368.54 m. The proposed SRS algorithm gives improved results with less mean elevation error of 1.8 m and the less standard deviation error of 4.85 m. Finally, the result reveals that the SRS algorithm performed better than other TomoSAR algorithms with the less relative error 0.003. [ABSTRACT FROM AUTHOR]

In this letter, an 11 GHz centered wideband absorptive frequency selective surface (FSS) design is presented. The absorptive FSS is dual polarized, and it has wide transmission band and a wide absorption band at the lower frequency side of the transmission band. An octagon shape with parallel microstrips toward center connected with lumped element resistors at the edges is proposed for the resistive layer unit element. Also, a multilayer octagon patch and aperture resonator are proposed for the wideband bandpass layer. As an alternative design method, the unit element of resistive layer of absorptive FSS is synthesized by a genetic algorithm code successfully. Genetic algorithm synthesis provides straightforward synthesis process compared to conventional method. Designed absorptive FSS is manufactured and frequency response is measured with WR‐90 waveguide setup. The measurement result of 1 dB transmission bandwidth is between 9.43 and 12.50 GHz with a minimum insertion loss of 0.65 dB. [ABSTRACT FROM AUTHOR]

In view of the increasing number of space objects, comprehensive high‐quality space surveillance becomes ever more important. Radar is a powerful tool that, in addition to detection and tracking of objects, also enables spatially high‐resolution imaging independent of daylight and most weather conditions. Together with the technique of Inverse Synthetic Aperture Radar (ISAR), very high‐resolution and distance‐independent two‐dimensional images can be obtained. However, advanced high‐performance radar imaging of space objects is a complex and demanding task, touching many technological and signal processing issues. Therefore, besides theoretical work, the Microwaves and Radar Institute of German Aerospace Center (DLR) has developed and constructed an experimental radar system called IoSiS (Imaging of Satellites in Space) for basic research on new concepts for the acquisition of advanced high‐resolution radar image products of objects in a low earth orbit. Based on pulse radar technology, which enables precise calibration and error correction, IoSiS has imaged space objects with a spatial resolution in the centimetre range, being novel in public perception and accessible literature. The goal of this paper is therefore to communicate and illustrate comprehensively the technological steps for the construction and successful operation of advanced radar‐based space surveillance. Besides the basic description of the IoSiS system design this paper outlines primarily useful theory for ISAR imaging of objects in space, together with relevant imaging parameters and main formulae. All relevant processing steps, necessary for very high‐resolution imaging of satellites in practice, are introduced and verified by simulation results. Finally, a unique measurement result demonstrates the practicability of the introduced processing steps and error correction strategies. [ABSTRACT FROM AUTHOR]

This paper illustrates an interferometric inverse synthetic aperture radar based on three‐dimensional imaging and rotational velocity estimation from a multistatic setup with three ground‐based radars with non‐orthogonal baselines. The radar backscattering along the orbit is simulated based on physical optics approximation. The paper illustrates a novel shape‐dependent and rotation‐invariant feature called normalised eigenvalues for classification. A database of interferometric point clouds is generated using radar back scattering at different aspect angles and classified using various classification algorithms. The classification accuracy at varying SNR levels was evaluated using Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

Space situational awareness systems primarily focus on detecting and tracking space objects, providing crucial positional data. However, understanding the complex space domain requires characterising satellites, often involving estimation of bus and solar panel sizes. While inverse synthetic aperture radar allows satellite visualisation, developing deep learning models for substructure segmentation in inverse synthetic aperture radar images is challenging due to the high costs and hardware requirements. The authors present a framework addressing the scarcity of inverse synthetic aperture radar data through synthetic training data. The authors approach utilises a few‐shot domain adaptation technique, leveraging thousands of rapidly simulated low‐fidelity inverse synthetic aperture radar images and a small set of inverse synthetic aperture radar images from the target domain. The authors validate their framework by simulating a real‐case scenario, fine‐tuning a deep learning‐based segmentation model using four inverse synthetic aperture radar images generated through the backprojection algorithm from simulated raw radar data (simulated at the analogue‐to‐digital converter level) as the target domain. The authors results demonstrate the effectiveness of the proposed framework, significantly improving inverse synthetic aperture radar image segmentation across diverse domains. This enhancement enables accurate characterisation of satellite bus and solar panel sizes as well as their orientation, even when the images are sourced from different domains. [ABSTRACT FROM AUTHOR]

In scenarios with constrained physical aperture sizes, aiming to enhance the resolution and accuracy of Direction of Arrival (DOA) estimation, this paper proposes a novel approach that integrates a moving synthetic virtual array with Sparse Bayesian Learning (SBL) for DOA estimation. Initially, a virtual array is constructed based on the motion characteristics of the target. Subsequently, the SBL method is employed to estimate the DOA of the target. Simulation experiments validate the effectiveness of this approach, demonstrating comparable DOA estimation performance to synthetic aperture methods with larger aperture sizes, even in situations with limited aperture expansion. Furthermore, under constant virtual aperture expansion, this method surpasses non‐SBL methods regarding DOA resolution. We explore the construction of a virtual array through the relative displacement induced by target motion. It further investigates the performance improvement of Direction of Arrival (DOA) estimation resolution using sparse Bayesian learning within the context of a virtual array. [ABSTRACT FROM AUTHOR]

Compared with optical remote sensing satellites, the geometric positioning accuracy of synthetic aperture radar (SAR) satellite is not affected by satellite attitude or weather conditions. SAR satellites can achieve relatively high positioning accuracy without ground control points, which is particularly important in global surveying and mapping. However, the stereo positioning accuracy of SAR satellites is mainly affected by the SAR systematic delay and the atmospheric propagation delay of radar signals. An iterative compensation method for the SAR systematic time delay is proposed based on digital elevation model to improve the stereo positioning accuracy of SAR satellites without control points. In addition, to address the non‐real‐time updates of external reference atmospheric param, an iterative compensation method to estimate the atmospheric propagation delay of radar signals is proposed based on standard atmospheric models. In this study, SAR images from the Gaofen‐3 (GF‐3) satellite with 5 m resolutions were used as experimental data to verify the effectiveness of our proposed method. Simultaneously, the 2D positioning accuracy was better than 3 m and increased by 42.9%, and the elevation positioning accuracy was better than 3 m and increased by 90.2%. [ABSTRACT FROM AUTHOR]

Classification with a few samples of training set has been a longstanding issue in the field of polarimetric synthetic aperture radar (PolSAR) image analysis and processing. Aiming at the small number of training samples of the PolSAR image classification task, a novel Self‐Supervised Ensemble Learning Framework (SSELF) is designed. The designed SSELF can automatically extract PolSAR features conducive to PolSAR image classification with a small number of training samples. In addition, it can significantly decrease the dependence of neural network algorithms on large labelled samples of training set. First, utilise the spatial–polarimetric features of PolSAR data perfectly, the EfficientNet‐B0 is presented and utilised as the main section of the Deep Learning (DL) model to extract DL features of PolSAR data. Then, using an optimisation function that constrains the cross‐correlation matrix of various distortions of each sample to the identity matrix, the designed DL model can obtain the effective features of homogeneous samples gathering and heterogeneous samples separating from each other in a self‐supervised manner. Moreover, following the great success of curriculum learning in the area of machine learning, a novel deep curriculum‐learning model is proposed, entitled Deep Curriculum Learning (DCL), to train the DL network in our self‐supervised model. The proposed DCL utilises the entropy‐alpha target decomposition to estimate the degree of complexity of each PolSAR image patch before applying it to the EfficientNet‐B0. Also, an accumulative mini‐batch pacing function is used to introduce more difficult patches to EfficientNet‐B0 in the training process of the designed self‐supervised model. Furthermore, two EL models, feature‐level and view‐level ensemble, are proposed to increase the feature extraction capability and classification result of PolSAR data by jointly using spatial features at different scales and polarimetric information at different bands. In fact, in the proposed feature‐level ensemble strategy, to improve the classification result, the extracted features of the different scales are used as the input of the designed feature fusion algorithm. Therefore, the extracted features are mapped to the new space with lower dimension. In general, in the proposed view‐level ensemble strategy, first, the Mutual Information (MI) between each feature and the other features calculates, and then based‐on the calculated MI, different group of features are selected as various views. Next, the final classification result of the PolSAR image classification is obtained by using the designed majority vote of the result in each view. It should be noted that unlike existing traditional methods, both amplitude and phase information of SAR images to devolve the training process of the proposed model are used. In addition, all of the parameters of the proposed network are developed to a complex domain. In addition, a complex backpropagation algorithm by using the gradient‐based model is used for training the network. Finally, experimental results on three well‐known PolSAR data sets illustrate that the designed SSELF can extract more discriminant features using the designed DL model and can achieve better classification results than the other six novel DL models in terms of small training samples and adequate labelled samples. [ABSTRACT FROM AUTHOR]

Coregistration is among the most important and challenging tasks when dealing with multiple synthetic aperture radar (SAR) images, especially when they are acquired at different time instants and characterised by low signal to noise power ratio (SNR) that contributes to their coherence reduction. However, even if some technological expedients could be implemented to maintain the same trajectory and to compensate for these inaccuracies during the acquisition campaign, multitemporal SAR images always need additional registration refinements after compression. Usually, to coregister a series of multitemporal SAR images, one of them is selected as the master, and the remainders are separately registered to it. Differently, in this study, a new strategy is developed to jointly coregister a stack of multitemporal SAR images. It is based on the exploitation of the cross‐correlations in turn computed from each couple of cross‐correlations (a.k.a. cross‐cross‐correlations) of the extracted patches. By doing so, the method is capable of exploiting also the respective misregistration information between the slaves during the estimation process. In this respect, this methodology is applied to enhance the registration capabilities of the constrained Least Squares (CLS) optimisation method, which instead does not account for the reciprocal information related to the slaves. Several tests are performed on multitemporal airborne‐measured SAR data. Obtained results show the effectiveness of the proposed algorithm in terms of achieved root mean square error for images affected by respective rotations also in comparison with the CLS counterpart. [ABSTRACT FROM AUTHOR]

The authors present exploitation of Multiple Views in Single‐Path (MVSP) Synthetic Aperture Sonar (SAS). The authors demonstrate the interest of MVSP SAS for underwater Mine Counter‐Measures (MCM) with unmanned vehicles, to comply with requirements for performances of detection and classification and time constraints. The authors here lay the emphasis on exploitation in reduction of false alarms of classification by alleviating the ambiguity between mines and natural bottom objects. Finally, the authors show that MVSP SAS is offering a pre‐identification tool with high impact on MCM process duration. [ABSTRACT FROM AUTHOR]

A novel dual‐polarization (DP) rectangular horn with equal elliptical beams for synthetic aperture radar application is proposed. The DP elliptical beams with same beam width are achieved by loading groove with coupling gap in the rectangular horn narrow side. The key parameters of the proposed horn are analyzed and a prototype operated at S band is fabricated and measured. Good agreements between simulated and measured results are obtained. What's more, an elliptical reflector antenna based on the proposed horn feed array is devised. Compared with the common rectangular horn, the reflector with the proposed horn owns better DP radiation performance. [ABSTRACT FROM AUTHOR]

Coherent change detection (CCD) takes advantage of the interferometric processing of synthetic aperture sonar (SAS) images and enables the detection of small scale changes to the scene between image pairs. This paper builds upon interferometric phase statistics developed for synthetic aperture radar and presents a method to differentiate between possible sources of decorrelation. A single‐pass pair of SAS images is categorized into four zones based on acoustic amplitude and coherence properties. Results suggest that regions of low coherence caused by a scene change can be differentiated from regions of low coherence due to other sources of decorrelation. Phase statistics could provide a technique to reduce the false alarm rate in CCD. Further studies are required to validate the approach for repeat‐pass SAS imagery and consider the effects of temporal decorrelation and misregistration errors on the phase distributions. [ABSTRACT FROM AUTHOR]

The usual procedure for extracting ocean surface information from data acquired from a high‐frequency surface wave radar transmitting from a floating platform is to first compensate for the motion of the antenna in the acquired motion‐contaminated Doppler spectrum and then extract the ocean wave parameters from the motion‐compensated result. The authors propose a new real‐time method to estimate the significant wave height directly from the antenna's received electric field in the time‐domain without requiring prior knowledge of the motion parameters or performing motion compensation. Based on the relation between the ocean surface displacement and the received electric field, this method calculates the significant wave height from the windowed variance of the upper envelope of the received electric field. A preliminary calibration is required, which can be carried out either by the deployment of a wave buoy or by analysing the data over a time period during which the sea state varies. The results from this simple proposed technique show that it may be used to estimate the significant wave height with a root‐mean‐square error (RMSE) between 10 and 14 cm over a wide range of significant wave height values. [ABSTRACT FROM AUTHOR]

Up‐to‐date topography data sets are essential for forecasting volcanic hazards and monitoring deformation. Digital elevation models are used to quantify eruption rates, used in flow modeling programs, and are necessary to accurately process interferometric synthetic aperture radar data for surface deformation. We can track topographic change at volcanoes through fieldwork, airborne instruments, and satellite data, with the last providing the greatest potential for global coverage. Despite this global coverage, we do not know the characteristics of topographic change at volcanoes over a given time interval. We define the specific acquisition needs for topography data using topographic change detected from recent eruptions. We review existing literature and compile a data set of eruptive products (121 lava flows, 99 domes and 163 pyroclastic density currents (PDCs)) from eruptions between 1980 and 2019. We find that different sensing capabilities are required for different use cases. A vertical accuracy of 1 m would detect 92% of all eruptive products including 100% of lava domes and lava flows, but only 78% of PDCs. A horizontal resolution of 13 × 13 m pixels is the minimum necessary to detect 90% of all eruptive products. Explosive eruptions (with PDC products) typically lasted less than 1 day and would need a temporal resolution of 1 day while a longer repeat interval is acceptable at effusive eruptions (lava domes and flows), which could last weeks to years. We find a lack of consistent data acquisition, with 45% of the 383 eruptive products reported not having published spatial dimensions. Plain Language Summary: Surface features in volcanic environments can change frequently, especially during an eruption. Volcanoes can create eruptive products such as lava and ash that change the surface features in the area. Accurate mapping of these surface features is important for tracking the progress of an eruption and for forecasting how the landscape will impact future volcanic hazards, such as lava flows or mudflows. We can track the changes of surface features through fieldwork, airborne instruments such as drones, or with various types of satellite data. We do not know how frequently we need to collect these data at volcanoes or with what spatial resolution. This work fills this knowledge gap through a literature review of the dimensions of products (lava flows, lava domes, and PDCs) erupted between 1980 and 2019. We suggest spatial and temporal resolutions to collect data on surface feature change at volcanoes. A pixel size of 13 m would measure 90% of products of volcanic eruptions and a vertical precision of 1 m would measure 92% of them. A temporal resolution of 1 day or less is needed for explosive eruptions, while a longer repeat interval is acceptable at eruptions with long‐lived lava flows. Key Points: Up‐to‐date topographic change data sets aid in forecasting eruption duration and eruptive hazardsWe suggest spatial and temporal resolutions to capture topographic change at volcanoes based on a review of past eruptive productsCurrent optical and commercial synthetic aperture radar satellites have the resolutions necessary to capture 90% of eruptive products studied [ABSTRACT FROM AUTHOR]

As a new algorithm to achieve sparse aperture inverse synthetic aperture radar (SA‐ISAR) imaging, the alternating direction method of multipliers (ADMM) suffers from selection of model parameters and the inability to discriminate the target and non‐target components. Therefore, an improved ADMM (I‐ADMM) algorithm is proposed to solve these problems. First, the particle swarm optimisation (PSO) algorithm is utilised to obtain the optimal model parameters. Aiming to adequately preserve the target's shape information in the ISAR image, a modified image entropy (IE) is proposed to be the objective function of the PSO. Then, a new regularisation function is obtained from the ADMM based ISAR image. The proposed algorithm can enhance the target components and suppress the non‐target components by utilising the regularisation function. Finally, results based on the simulated and measured data show that the proposed I‐ADMM algorithm not only achieves at least 9.4% improvement in IE but also greatly improves the image quality as visually compared with the traditional ADMM algorithm which validates the effectiveness and superiority of the proposed algorithm. [Correction added on 13/09/23, after first online publication: In the following sentence in abstract "Finally, results based on... the proposed algorithm." 10% was changed as 9.4%.] [ABSTRACT FROM AUTHOR]

Polarimetric Airborne Scientific INstrument, mark 2 (PASIN2) is a 150 MHz coherent pulsed radar with the purpose of deep ice sounding for bedrock, subglacial channels and ice‐water interface detection in Antarctica. It is designed and operated by the British Antarctic Survey from 2014. With multiple antennas, oriented along and across‐track, for transmission and reception, it enables polarimetric 3D estimation of the ice base with a single pass, reducing the gridding density of the survey paths. The off‐line data processing stream consists of channel calibration; 2D synthetic aperture radar (SAR) imaging based on back‐projection, for along‐track and range dimensions; and finally, a direction of arrival estimation (DoA) of the remaining across‐track angle, by modifying the non‐linear MUSIC algorithm. Calibration flights, during the Antarctic Summer campaigns in 16/17 and 19/20 seasons, assessed and validated the instrument and processing performances. Imaging flights over ice streams and ice shelves close to grounding lines demonstrate the 3D sensing capabilities. By resolving directional ambiguities and accounting for reflector across‐track location, the true ice thickness and bed elevation are obtained, thereby removing the error of the usual assumption of vertical DoA, that greatly influence the output of flow models of ice dynamics. [ABSTRACT FROM AUTHOR]

The Institute of Polymer Chemistry at Nankai University in China recently celebrated its 40th anniversary. The institute, founded in 1984 by Professor Binglin He, has become a well-established research institution with a focus on polymer synthetic chemistry, polymer physics, and the correlation between structure and properties in new functional polymer materials. It has 62 faculty members and offers master's and doctoral programs in polymer chemistry. The institute has published over 1000 research papers and received numerous awards for its contributions to polymer science. The special issue of Macromolecular Rapid Communications features 25 publications highlighting the institute's research in polymer science. The institute hopes that this publication will encourage more collaborations with institutions worldwide in the future. [Extracted from the article]

It is difficult for a convolutional neural network (CNN) to capture the detailed features of synthetic aperture radar (SAR) images when increasing the network depth. To capture sufficient information for reconstructing image details, the authors propose a multidirectional and multiscale convolutional neural network (MMCNN) in which the wavelet subband is input into each independent subnetwork to be trained. Each subnetwork has few convolution layers and a loss function. When the loss function reaches its optimal value, all subbands are integrated to produce the despeckled SAR image through the inverse Wavelet transform. The proposed MMCNN consisting of multiple subnetworks extracts the detailed features and suppresses speckle noise from different directions and scales; thus, its performance is improved by broadening the network width rather than increasing the depth. Experimental results on synthetic and real SAR images show that the proposed method shows superior performance over the state‐of‐the‐art methods in terms of both quantitative assessments and subjective visual quality, especially for strong speckle noise. [ABSTRACT FROM AUTHOR]

Due to the limitation of traditional microlens arrays (MLAs) in integral imaging display, the depth of field (DOF) is restricted in space and the center depth plane is difficult to extend in a large range. Here, we propose a microfabrication method based on bifocal MLAs to improve DOF. The bifocal MLAs for extended DOF were fabricated by using two‐step photolithography and thermal reflow. This method allows diverse microlenses of high to low numerical aperture to achieve high spatial resolution as well as accurate depth estimation. Microlenses of different focal lengths were simultaneously deposited on a substrate by repeated photolithography with multiple photomasks with alignment mark to define micro‐posts of different thicknesses. Hexagonally packaged bifocal MLAs clearly show the DOF extended from 0.004 to 4.908 mm for 57.6 μm in lens diameter, and their corresponding object distance ranges from 0.125 to 0.165 mm. Based on the proposed scheme, this method provides potential applications in integral imaging 3D display or light field display. [ABSTRACT FROM AUTHOR]

On June 21st, a Mw6.2 earthquake struck the Afghan‐Pakistan‐border‐region, situated within the India‐Asia collision. Thousand thirty‐nine deaths were reported, making the earthquake the deadliest of 2022. We investigate the event's rupture processes by combining seismological and geodetic observations, aiming to understand what made it that fatal. Our Interferometric Synthetic Aperture Radar‐constrained slip‐model and regional moment‐tensor inversion, confirmed through field observations, reveal a sinistral rupture with maximum slip of 1.8 m at 5 km depth on a N20°E striking, sub‐vertical fault. We suggest that not only external factors (event‐time, building stock) but fault‐specific factors made the event excessively destructive. Surface rupture was favored by the rock foliation, coinciding with the fault strike. The distribution of Peak‐Ground‐Velocity was governed by the sub‐vertical fault. Maximum slip was large compared to other events globally and might have resulted in peak‐frequencies coinciding with resonance‐frequencies of the local buildings and demonstrates the devastating impact of moderate‐size earthquakes. Plain Language Summary: The June 2022 devastating M6.2 Afghanistan earthquake has caused a high depth toll, making it the deadliest earthquake of 2022. This is notable and partly intriguing as the earthquake size is much smaller than other events that happened in 2022. Therefore, we combine a range of geophysical, geodetic and geological methods to understand how exactly the subsurface ruptured during the earthquake. We suggest that it was a combination of the local circumstances (the event time, as it hit at night time, and the building stock) and the geometry of the rupture surface together with the local geology that made this event particularly deadly. More generally, this study shows the excessive hazard and impact caused by moderate‐size earthquakes. Key Points: We combine Interferometric Synthetic Aperture Radar, moment tensor inversion, field mapping and Peak‐Ground‐Velocity (PGV) simulations to investigate the rupture processesThe event had a sinistral rupture with maximum slip of 1.8 m at 5 km depth on a N20°E striking, sub‐vertical faultCoincidence of large slip, fault geometry and alignment of rock foliation with strike enhanced PGV and the destructiveness of the event [ABSTRACT FROM AUTHOR]

Synthetic aperture sonar image reconstruction relies on the coherence of overlapping phase centres to provide accurate micronavigation for a sensed scene. It is shown that phase centres lose coherence for near‐range scattering from large synthetic aperture sonar arrays due to the fundamentally bistatic nature of these sensors. This effect is modelled using the van Cittert‐Zernike theorem and a point‐based sonar scattering model. Reduction of the window length used in the delay estimation process can partially mitigate the loss of coherence at the expense of increased variance in the resulting delay estimates. [ABSTRACT FROM AUTHOR]

Background: Approximately 500 000 patients present with critical limb ischemia (CLI) each year in the U.S., requiring revascularization to avoid amputation. While peripheral arteries can be revascularized via minimally invasive procedures, 25% of cases with chronic total occlusions are unsuccessful due to inability to route the guidewire beyond the proximal occlusion. Improvements to guidewire navigation would lead to limb salvage in a greater number of patients. Purpose: Integrating ultrasound imaging into the guidewire could enable direct visualization of routes for guidewire advancement. In order to navigate a robotically‐steerable guidewire with integrated imaging beyond a chronic occlusion proximal to the symptomatic lesion for revascularization, acquired ultrasound images must be segmented to visualize the path for guidewire advancement. Methods: The first approach for automated segmentation of viable paths through occlusions in peripheral arteries is demonstrated in simulations and experimentally‐acquired data with a forward‐viewing, robotically‐steered guidewire imaging system. B‐mode ultrasound images formed via synthetic aperture focusing (SAF) were segmented using a supervised approach (U‐net architecture). A total of 2500 simulated images were used to train the classifier to distinguish the vessel wall and occlusion from viable paths for guidewire advancement. First, the size of the synthetic aperture resulting in the highest classification performance was determined in simulations (90 test images) and compared with traditional classifiers (global thresholding, local adaptive thresholding, and hierarchical classification). Next, classification performance as a function of the diameter of the remaining lumen (0.5 to 1.5 mm) in the partially‐occluded artery was tested using both simulated (60 test images at each of 7 diameters) and experimental data sets. Experimental test data sets were acquired in four 3D‐printed phantoms from human anatomy and six ex vivo porcine arteries. Accuracy of classifying the path through the artery was evaluated using microcomputed tomography of phantoms and ex vivo arteries as a ground truth for comparison. Results: An aperture size of 3.8 mm resulted in the best‐performing classification based on sensitivity and Jaccard index, with a significant increase in Jaccard index (p < 0.05) as aperture diameter increased. In comparing the performance of the supervised classifier and traditional classification strategies with simulated test data, sensitivity and F1 score for U‐net were 0.95 ± 0.02 and 0.96 ± 0.01, respectively, compared to 0.83 ± 0.03 and 0.41 ± 0.13 for the best‐performing conventional approach, hierarchical classification. In simulated test images, sensitivity (p < 0.05) and Jaccard index both increased with increasing artery diameter (p < 0.05). Classification of images acquired in artery phantoms with remaining lumen diameters ≥ 0.75 mm resulted in accuracies > 90%, while mean accuracy decreased to 82% when artery diameter decreased to 0.5 mm. For testing in ex vivo arteries, average binary accuracy, F1 score, Jaccard index, and sensitivity each exceeded 0.9. Conclusions: Segmentation of ultrasound images of partially‐occluded peripheral arteries acquired with a forward‐viewing, robotically‐steered guidewire system was demonstrated for the first‐time using representation learning. This could represent a fast, accurate approach for guiding peripheral revascularization. [ABSTRACT FROM AUTHOR]

Synthetic aperture radar tomography (TomoSAR) baseline optimization method is capable of reducing system complexity and improving the temporal coherence of data, which has become important research in the field of TomoSAR. A nested TomoSAR technique is proposed, which introduces the nested array into TomoSAR as the baseline configuration. This technique obtains uniform and continuous difference co‐array through the nested array to increase the degrees of freedom of the system and expands the virtual aperture along the elevation direction. In order to make full use of the difference co‐array, covariance matrix of the echo needs to be obtained. Therefore, a TomoSAR sparse reconstruction algorithm based on the nested array is proposed, which uses adaptive covariance matrix estimation to improve the estimation performance in complex scenes. The effectiveness of the proposed method through simulated and real data experiments is demonstrated. Compared with traditional TomoSAR and coprime TomoSAR, the imaging results of this proposed method have better anti‐noise performance and retain more image information. [ABSTRACT FROM AUTHOR]

Synthetic aperture sonar (SAS) interferometry is a technique for very high resolution imaging and mapping of the seabed. In SAS interferometry, the seabed depth estimation performance is a function of the system, the geometry, the signal-to-noise ratio (SNR) and the filter size, equivalent to the achieved horizontal resolution. A strong driver for SNR is the imaging range and grazing angle. The variation of these parameters over a typical SAS swath gives rise to a large variation in the depth estimation performance. To mitigate the negative effect of this, we suggest to use an adaptive phase estimation filter size, such that the standard deviation of the depth estimate is proportional to the horizontal resolution. We demonstrate the suggested adaptive filter size method on long range data collected using a HUGIN Superior autonomous underwater vehicle (AUV) equipped with a HISAS 1032 Dual receiver interferometric SAS. Our technique increases the valid area coverage when the SNR is marginal, at the expense of reduced horizontal resolution [ABSTRACT FROM AUTHOR]

Nowadays, polarimetric interferometric synthetic aperture radar (PolInSAR) has attracted increasing attention for the simultaneous acquisition of scattering and terrain information. The scattering mechanism vectors corresponding to the optimal coherences have shown great effect in land cover classification and forest mapping. To extract scattering mechanism vectors, different optimization algorithms are proposed but always accompanied with spatial discontinuities. This letter proposes a method to optimize scattering mechanism vectors based on nonlocal estimations. A pixel‐by‐pixel optimization model is established by calculating patch‐based nonlocal similarity, which effectively reduces the uncertainty of scattering mechanism vector estimation while maintaining high resolution. The phase recovery experiment is conducted on simulated data and the root mean square errors (RMSEs) of three algorithms are compared. The proposed method performs better with a RMSE of 0.22 in the whole image, against 0.25 and 1.27 for other algorithms. The recovery results in the target region (RMSE 0.11 against 0.21 and 0.99) and linear edge region (RMSE 0.26 against 0.49 and 1.52) also indicate strong ability in detail preservation. Then the observed ESAR data is utilized for further assessment. It demonstrates that the proposed method has a significant improvement to reduce singularities and distinguish artificial buildings. [ABSTRACT FROM AUTHOR]

Owing to the time variance of the inverse synthetic aperture radar (ISAR) imaging plane of space targets, scatterers with large heights relative to the imaging plane migrate through several Doppler cells. This defocussing in the azimuth direction of each scatterer cannot be compensated via the traditional migration through the resolution cell (MTRC) compensation method because the height of each scatterer is quite different and independently distributed in the ISAR image. In this study, a parametric azimuth‐defocussing model‐based CLEAN method is proposed for the space‐target ISAR image. First, high‐order defocus parameters and their influences on the image of space targets were analysed at different arc segments. Subsequently, a mathematical azimuth‐defocussing expression of the ISAR image scatterers was derived after MTRC and azimuth high‐order phase compensation, and an approximate defocus expression based on the Fresnel integral was provided for computational efficiency. This model can estimate the complex amplitude, coordinates and defocus parameters of each scatterer in the image domain by applying a sequential quadratic programing algorithm. Finally, the validity and stability of the proposed algorithm for the isolated and coupled scatterer extraction were verified at different signal‐to‐noise ratios, and different defocus parameters were verified through simulations. [ABSTRACT FROM AUTHOR]

Spaceborne interferometric synthetic aperture radar (InSAR) technology is an effective method to obtain digital elevation model (DEM) data. The bistatic InSAR configuration of the inclined‐geosynchronous (InGEO) transmitter with low earth orbit (LEO) receivers (InGEO‐LEO) is a novel InSAR system to acquire terrain information. This novel system is characterised with high resolution, wide swath and timeliness, but the Newton iterative method is time‐consuming to solve the bistatic InSAR equations for fast DEM generation. For the conventional LEO bistatic InSAR system, the closed‐form solution is an effective method to improve the efficiency of solving InSAR equations, which is invalid in the InGEO‐LEO InSAR system because of the significant geometry difference caused by the orbits of InGEO transmitter and LEO receivers. To address this issue, we analyse the bistatic InGEO‐LEO geometry in detail and exploit the bistatic InSAR equations to propose an approximate closed‐form solution (ACS) for the novel system. Compared with the general Newton iterative method, the ACS significantly improves the efficiency of geolocation for the bistatic InGEO‐LEO InSAR system with high precision. Simulation experiments are carried out to verify the effectiveness and superiority of ACS. [ABSTRACT FROM AUTHOR]

Due to the aircraft targets' uncooperative character, acquiring the complete scattering characteristics of enemy aircraft is challenging. An effective reconstruction method of target scattering centres based on characteristics analysis of inverse synthetic aperture radar (ISAR) images is proposed in this letter. First, a positive definite manifold characterizing ISAR images of different attitudes is constructed. Then, Kullback–Leibler divergence is used as a measure of the variability between ISAR images. Finally, an ISAR image interpolation method based on the characteristics analysis of ISAR images is proposed to obtain the scattering characteristics with more attitudes. Furthermore, simulation results confirm that the proposed method is effective. [ABSTRACT FROM AUTHOR]

This article presents a novel 3‐D shape reconstruction strategy for small solar system bodies using spaceborne radar which is applied in flyby trajectories to characterize multiple targets in one mission to save time and cost. In this study, we establish a measurement geometry for rapidly spinning small solar system bodies that combines the motion properties of synthetic aperture radar and circular synthetic aperture radar techniques. We also propose a modified imaging algorithm, which is processed using Cardano's formula and the modified polar format algorithm, to improve the imaging quality. Finally, we present simulated results of point‐scattering and 3D shape models. Our analysis shows that the shape reconstruction errors of the algorithm are less than 1.5 m as indicated by the standard deviation. Plain Language Summary: Exploring small solar system bodies is crucial to understanding the evolution of our solar system. However, most of these small bodies are distant from Earth, and the small size, weak gravity, irregular shape, and high speed rotation further increase the difficulty of exploring a small solar system body. To tackle these challenges and characterize as many targets as possible in one mission, we propose a novel 3‐D imaging strategy. Our approach aims to reconstruct the 3D shape of rapidly spinning small solar system bodies in flyby trajectories. We begin by establishing an observation model and analyzing the imaging geometry and signal characteristics. Next, we describe our reconstruction procedure in detail and propose a modified algorithm to improve the imaging quality. Finally, we present simulated results to validate our proposed method. Key Points: A new three‐dimensional shape reconstruction strategy is presented for rapidly spinning small solar system bodies in flyby missionsA modified imaging algorithm to compensate the phase errors to optimize the image quality is provided [ABSTRACT FROM AUTHOR]

A method for time‐domain motion compensation of high frequency (HF) radar signals for the case of a floating transmitter and fixed receiver is proposed when the motion parameters (including the amplitude and angular frequency of the motion) are not known a priori. In this study, the floating platform is assumed to follow a single‐frequency motion model. Additionally, instead of trying to estimate platform motion parameters from the received motion‐contaminated Doppler spectrum, which is proportional to the observed radar cross‐section of the ocean surface from the floating platform, the motion parameters from the autocorrelation function of the received electric field are estimated, which is related to the received radar cross‐section by application of an inverse temporal Fourier transform. By comparing the locations of the zeros of the autocorrelation function for the fixed antenna case with that for an antenna on a floating platform and finding the zeros associated with the platform motion, the motion parameters are estimated. These parameters are matched with actual motion parameter values, from which the motion‐compensated Doppler spectrum is recovered from the Doppler spectrum of the antenna on a floating platform. [ABSTRACT FROM AUTHOR]

We employ a time series of Sentinel‐1 differential radar interferometry data from 2018 to detect the variability in grounding line position of the Fisher, Mellor, and Lambert glaciers, which drain about 47 billion tons of ice per year from East Antarctica. We observe kilometer‐scale tidal migration, two orders of magnitude larger than expected for ice flowing over a hard bed. The migration is not in phase with changes in oceanic tide. In two estuaries underlaid by subglacial channels, we observe two states of migration that switch on and off over time scales of several weeks. The range of vertical motion reveals a water column thickness of 2–20 cm. Such intrusions of seawater over wide grounding zones are not accounted for in physical models. Including them will add vigorous melting of grounded ice that will enhance the sensitivity of glaciers to ocean warming and increase projections of mass loss. Plain Language Summary: Grounding lines (GLs) are assumed to migrate back and forth with changes in oceanic tides based on hydrostatic equilibrium, which induces horizontal migration in the range of a few 100 m, similar to the spatial resolution of ice sheet models. Differential radar interferometry data from the Sentinel‐1 mission, however, reveals that for the Fisher, Mellor, and Lambert glaciers, the migration is two orders of magnitude larger. Such widespread intrusions of seawater will melt grounded ice and affect the regime of basal friction of glaciers and their stability. Physical models in charge of projecting sea level rise assume a fixed GL, with zero melt. We report regions of enhanced migration (10–15 km) along estuaries underlaid by subglacial channels where water gets trapped for several weeks before draining out. These irregular, widespread interactions between ice and seawater will have a strong impact on glacier evolution and projections if implemented in physical models. Key Points: The zone of tidal variability of Amery Ice Shelf grounding line (GL) is two orders of magnitude wider than expected from hydrostatic equilibriumWe detect GL migration uncorrelated with tide up to 15 km upstream, along subglacial troughs, with 2–20 cm thick water intrusionsSeawater intrusion in estuaries has high potential for melting ice in grounding zone and enhance sensitivity of glaciers to ocean warming [ABSTRACT FROM AUTHOR]

Earth Observation Satellite (EOS)‐04 launched on 14 February 2022, carries a C‐band Synthetic Aperture Radar (SAR) for Agriculture, Forestry, Hydrology, and Flood mapping applications. In this paper, we have used C‐band SAR images and near‐simultaneous observations from the global precipitation measurements (GPM) to study the signatures of multiple convective rain cells. The bright patches are found on C‐band SAR imagery, which depicts the information of hydrometeors such as graupels or hails in the melting layer. For the first time, unambiguously estimated the diameter of the convective core rain cells from the C‐band SAR backscattered signal and compared with near‐simultaneous observations from GPM‐GMI and Ku‐band radar to confirm our findings. Thus, the present study demonstrates the potential of C‐band SAR for identifying the signatures of convective rain cells. Plain Language Summary: Earth Observation Satellite‐04 launched on 14 February 2022, carries a C‐band Synthetic Aperture Radar (SAR) for Agriculture, Forestry, Hydrology, and Flood mapping applications. The Convective clouds produce a significant amount of precipitation, and the signature of convective rain cells appeared as bright oceanic patches on the SAR imagery. The present study demonstrates the potential of C‐band SAR for the signatures of convective rain cells and near‐simultaneous observations from global precipitation measurements to confirm our findings. Key Points: The present study brought out the signatures of convective rain cells using C‐band Synthetic Aperture Radar (SAR) onboard Earth Observation Satellite ‐04 satelliteFor the first time, unambiguously estimated the diameter of the convective core rain cells from the C‐band SAR backscattered signalWe compared near‐simultaneous observations from GPM‐GMI and Ku‐band precipitation radar to confirm the present findings [ABSTRACT FROM AUTHOR]

Groundwater withdrawal can cause localized and rapid poroelastic subsidence, spatially broad elastic uplift of low amplitude, and changes in the gravity field. Constraining groundwater loss in Mexico City, we analyze data from the Gravity Recovery and Climate Experiment and its follow‐on mission (GRACE/FO) and Synthetic Aperture Radar (SAR) Sentinel‐1A/B images between 2014 and 2021. GRACE/FO observations yield a groundwater loss of 0.85–3.87 km3/yr for a region of ∼300 × 600 km surrounding Mexico City. Using the high‐resolution interferometric SAR data set, we measure >35 cm/yr subsidence within the city and up to 2 cm/yr of uplift in nearby areas. Attributing the long‐term subsidence to poroelastic aquifer compaction and the long‐term uplift to elastic unloading, we apply respective models informed by local geology, yielding groundwater loss of 0.86–12.57 km3/yr. Our results suggest Mexico City aquifers have been depleting at faster rates since 2015, exacerbating the socioeconomic and health impacts of long‐term groundwater overdrafts. Plain Language Summary: Groundwater overdraft in Mexico City results from excessive freshwater demand and unsustainable water resource management in a subtropical environment with warm summers and dry winters. Groundwater depletion can result in ground surface deformation and changes in the gravity field, observable by Sentinel‐1 and GRACE satellites. Here, we examine data from both satellite missions between November 2014 and October 2021 to determine groundwater volume loss. Using GRACE, which has a footprint of ∼350 km, we quantify groundwater volume loss to a rate of 0.85–3.87 km3 per year in the broader area surrounding Mexico City. Analysis of high‐resolution Sentinel‐1 synthetic aperture radar images shows land sinks at a rate of 35 cm/yr within the city and surrounding areas uplifts at a rate of ∼2 cm/yr. While the subsidence is a consequence of aquifer compaction, the uplift represents an elastic unloading response of the Earth's crust to water mass loss. Using geophysical models informed by local geology, we show that the region loses groundwater at rates of 0.86–12.57 km3/yr. Our results emphasize the need for groundwater monitoring in Mexico City to assist with managing freshwater resources. Key Points: A subsidence rate of >35 cm/yr within Mexico City, surrounded by ∼2 cm/yr of uplift, is observed using space‐borne synthetic aperture radarGroundwater loss of 0.86–12.57 km3/yr in Mexico City causes poroelastic subsidence, a broad‐scale elastic uplift, and gravity field changeMexico City aquifers have been depleting at least since 2015, exacerbating groundwater overdrafts' socioeconomic and health impacts [ABSTRACT FROM AUTHOR]

Fourier ptychographic microscopy (FPM) is a computational high‐throughput technique for high‐resolution and wide field‐of‐view (FOV) imaging applications such as cell biology, medicine screening, and digital pathology. By integrating angle‐varied illumination, iteration phase retrieval, and synthetic aperture, it achieves a significantly enhanced imaging resolution beyond the diffraction limit of the objective lens while retaining its original large FOV without any mechanical movement. However, sufficient data redundancy is a prerequisite for the convergence of the iteration algorithm, which in turn requires dozens or even hundreds of raw images to get a decent resolution, leaving ample room for further improvement. In this paper, an efficient synthetic aperture scheme for FPM is proposed, termed ESA‐FPM. It employs both coherent and incoherent illuminations to maximize the efficiency of data utilization and achieve high spatial‐bandwidth product (SBP) reconstruction with few acquisitions. The data redundancy requirements are further analyzed, suggesting that ESA‐FPM reaches imaging resolution of 3NAobj$3NA_{\rm obj}$ using only seven images. The experiment with USAF target demonstrates that ESA‐FPM achieves theoretical resolution with only 1.6% of the data of conventional FPM. A customized miniaturized ESA‐FPM system with a high‐numerical‐aperture, low‐magnification objective lens, and a high‐brightness LED array is built, demonstrating its potential for biomedical and pathological applications. [ABSTRACT FROM AUTHOR]

In order to recover the three‐dimensional (3D) structure of the target from sequential inverse synthetic aperture radar (ISAR) images, the factorisation method is generally used. It requires a large number of high‐quality matched feature points from different ISAR images. If the number of extracted feature points is insufficient, the restored 3D structure is not obvious. Furthermore, the mismatching of feature points will greatly affect the quality of target reconstruction. However, the factorisation method only uses the information from the ISAR images, while that from imaging geometry is not sufficiently considered. ISAR imaging is a kind of projection, and the projection plane information could be taken into account for the 3D reconstruction. Hence, a new 3D reconstruction method for stable targets from sequential ISAR images is proposed in this paper. Firstly, the ISAR images are preprocessed with the CLEAN algorithm. The maximum between‐cluster variance method is applied to extract feature points from the processed images. Moreover, the image projection plane and projection equation corresponding to different ISAR images are analysed by using imaging geometry information. According to the projection equation, the feature points are back‐projected (BP) to the 3D space. Finally, the 3D point clouds obtained by the BP from multiple radar images are fused by the iterative closest point algorithm to restore the 3D structure of the target. The simulation and experiment results show the effectiveness and robustness of this method. [ABSTRACT FROM AUTHOR]

Generalisation of one‐dimensional dictionary learning (1DDL) algorithms to Multidimensional (MD) mode and its utilisation in MD data applications, increases the speed and reduces the computational complexity. An example of such an application is 3D inverse synthetic aperture radar (ISAR) image reconstruction and noise reduction. In this study, in addition to MD mode generalisation, the formulation structure of the multidimensional dictionary learning (MDDL) problem is discussed followed by two novel algorithms to solve it. The first one is based on the K‐singular value decomposition algorithm for 1DDL, which uses alternating minimisation and singular value decomposition. The second algorithm is the extension of the sequential generalisation of K‐means 1DDL algorithm to the MD mode. Moreover, the MD tensor denoising method based on the MDDL algorithm (MDDL‐ALG) is proposed. As an application, the proposed method is used to denoise the 3D ISAR image. The numerical simulations reveal that the proposed methods, in addition to reducing the memory consumption and the computational complexity, also enjoy higher convergence rate in comparison to 1D algorithms. Specifically, convergence speed of MD algorithms, depending on the training data size, is up to at least 10 times faster than the equivalent 1D counterparts. As revealed through the simulations, the amount of signal to noise ratio recovered by the proposed methods is almost 2 dB higher than the case using a pre‐designed dictionary for denoising. Moreover, it outperforms about 10 dB over the case with the conventional 3D‐IFFT method for image construction. [ABSTRACT FROM AUTHOR]

Using electrically large antennas for array applications may cause grating lobes and this can change the array pattern. To achieve a low side lobe level for boresight pattern for linear or planar array antennas, in the literature it is seen that the common method is the use of feeding each antenna with some amplitude distribution and keeping the distance between the antennas less than a wavelength. However, in this study the distance between the antennas is chosen to be greater than a wavelength. Therefore, the common methods cannot be used. To achieve a low side lob level in the radiation pattern for an array of antennas composed of antennas with a distance greater than one wavelength. The aperture length of each antenna is chosen to be variable and an analytical solution method is used to calculate the amplitude of each aperture field of the horn antennas. Thus, the determination of unit horns' optimal aperture lengths Li can be considered a multivariable optimization problem. This challenging problem was achieved using a novel meta‐heuristic optimization algorithm called the differential evolutionary algorithm (DEA), where the aperture lengths of each array element are taken as inputs to find the optimal side lobe level (SLL). Based on the obtained solutions, a 4 × 1 horn array antenna design alongside its feed network was designed for Ku‐band applications. The design of the array is simulated in CST simulation software, and the obtained simulated results had been compared with experimental results and counterpart designs in the literature. [ABSTRACT FROM AUTHOR]

Direction of arrival (DOA) estimation of mixed near‐field (NF) and far‐field (FF) signals is one of the key issues in the study of array signal processing. For more precise localisation performance, sparse arrays have drawn the attention of an increasing number of academics. Excitingly, sparse arrays enable larger array apertures and higher degrees of freedom (DOFs) than traditionally used uniform linear arrays. Consequently, this study proposes a transformed symmetric nested array (TSNA) for the passive localisation application regarding mixed NF and FF. There are three processes that go into building the proposed array. In the first step, we swap the positions of the uniform linear arrays and the sparse linear arrays in the nested array. In the second step, we place the corresponding array sensors extracted from the uniform linear array behind the uniform linear array to form a new subarray. In the last step, the TSNA is constructed by folding the formed array in half. Furthermore, we give the formula of the largest consecutive lags of the TSNA and its corresponding constructor. Finally, through theoretical analysis and computer performance simulation, this study illustrates the proposed array's numerous advantages over currently used symmetric sparse arrays. [ABSTRACT FROM AUTHOR]

This letter proposes an improved synthetic aperture imaging algorithm to enhance the imaging performance in the Azimuth Missing Data (AMD) case. The proposed algorithm designs an effective phase compensation function based on the Range Cell Migration Correction (RCMC) echo and first reconstructs the complete RCMC echo from the AMD echo. The accuracy of echo reconstruction is improved, leading to a better imaging result. Numerical simulations and a real measured experiment verify the effectiveness of the proposed algorithm. Furthermore, since the range positions of targets can be located after RCMC processing, only non‐zero RCMC signals are reconstructed. Thus, the computational complexity superiority of the proposed algorithm is obvious, especially when the targets are sufficiently sparse in the range direction. [ABSTRACT FROM AUTHOR]

The use of Multiple Input Multiple Output (MIMO) orthogonally coded waveforms sharing the same bandwidth, has the potential to increase area coverage rate in synthetic aperture sonar (SAS). The disadvantage is cross‐talk between the waveforms. In this letter, the benefits and limitations are listed for a best case use of MIMO in SAS. A scheme is developed to emulate a MIMO system with realistic cross‐talk that can be tested on non‐MIMO SAS data. The impact of cross‐talk is evaluated on simulated data and real data collected by a HISAS interfereometric SAS carried by a HUGIN autonomous underwater vehicle. The finding is that the negative impact of cross‐talk on SAS is significant. [ABSTRACT FROM AUTHOR]

In the Garhwal Himalaya, the steeply inclined Main Boundary Thrust (MBT) is characterized by landforms that indicate towards tectonic activity in the recent past. Linear active fault trace, sub‐recent fault scarps, strath terrace, uplifted terraces, deflected drainage, and triangular facet cones are some of the morphotectonic evidences of recent tectonic activity along the MBT. The MBT is defined by active fault trace in the form of linear depression and shows a prominent slope break across it. Thrusting of the Lesser Himalayan bedrocks over the colluvial deposits and back tilting of the colluvial deposits are also observed in the MBT zone. The formation of the sag pond and the deposition of the Quaternary lacustrine sediments followed by the deformation of the lacustrine deposits indicate phases of tectonic activities along the MBT. The later phase of deformation is represented by the folded lacustrine and colluvial deposits, where the amplitude of the fold measures about 3 m‐high and the deformed section measures about 23 m in length. The ongoing deformation patterns of the MBT zone have also been monitored with the help of Synthetic Aperture Radar‐based time series analysis. We used Sentinel‐1C dataset in ascending direction with polarization of the VV+ VH acquired between December 2, 2017 to September 7, 2021 to identify phase changes caused by ongoing active deformation. The Persistent Scatterer Interferometry (PSI) result based on Sentinel‐1A suggests that the Dehradun–Mussoorie and adjoining region has undergone an average deformation of 5.5 to −11 mm/year and the ground displacement of 1.5 to −3.8 cm. The time series analysis reveals that the Mussoorie hills in the MBT zone have higher rate of deformation. [ABSTRACT FROM AUTHOR]

Sparse inverse synthetic aperture radar (ISAR) imaging can be generally achieved by compressed sensing (CS) methods because sparse sampling disables the approach of conventional range Doppler. However, the CS‐based methods have to convert the matrix into a vector when the random sampling is adopted, which results in huge memory usage and high computational complexity. Note that matrix completion (MC) is suitable for matrix operations, which can recover random sparse data directly based on the low‐rank property of the echo matrix. In order to improve the performance of the conventional MC approaches, a novel reweighted matrix completion method for sparse ISAR imaging is proposed in this paper. To avoid using the same singular value thresholding of the traditional MC method to achieve a low‐rank solution, the reweighted scheme for singular values is applied to restrain the rank. Furthermore, the weights of the current iteration are updated with their singular values obtained in the former iteration, rather than using a fixed value. Then, the alternating direction method of multipliers is utilised to alternatively optimise the proposed model, which has an improved computational efficiency. Once the full data is recovered, the ISAR image can be achieved via the conventional 2D inverse fast Fourier transform. Experimental results based on measured data validate the proposed approach that can result in improving imaging performance within several seconds, which is tens of times faster than some reported low‐rank‐based methods. [ABSTRACT FROM AUTHOR]

The motion of targets is well known to result in their defocusing and displacement in SAR imagery, but detection of motion and re‐focusing of targets under generic conditions remains an ongoing interest. One class of methods involves forming images of sub‐apertures in which motion defocusing will be reduced. In this paper, dynamic tomographic image formation methods utilising an optical flow constraint is used to form a video of SAR sub‐aperture images. These retain fine resolution of the full aperture, focusing along‐track motion. [ABSTRACT FROM AUTHOR]

Based on Chebyshev polynomials, the two‐way slant range is first approximated by the fourth‐order polynomial approximation. With the series reversion method, the point target reference spectrum (PTRS) which is further used for the development of imaging algorithm in this letter is obtained. The presented method processes the echoed signal corresponding to each transmitter/receiver pair. And then a high‐resolution synthetic aperture sonar (SAS) image is obtained by coherently superposing all coarse‐resolution images. Comparing the peak sidelobe ratio (PSLR) and integration sidelobe ratio (ISLR), the performance of the presented method is superior to that of the traditional method. Simulations are further validated by the presented method. [ABSTRACT FROM AUTHOR]

Internal waves (IWs) are a widely occurring phenomenon in the global oceans. They have significant impacts on marine environments through their propagation mechanisms. In this study, we collect 390 satellite images with 775 labels from Sentinel-1 Synthetic Aperture Radar (SAR) from 2014 to 2021 to construct a data set containing IW packets in Andaman Sea, South China Sea, Sulu Sea, and Celebes Sea, respectively. All the SAR images acquired are pre-processed to provide clear IW packets for better visualization. To better detect IWs in global oceans automatically, a machine-learning based model is proposed to focus on different channels and the spatial information. The precision, recall, and mean average precision of our improved model applied on the IW data set is up to 98.7%, 96.9%, and 98.9%, respectively. Various cases of IWs images are analyzed to illustrate detection quality in different stripes, scales, and propagation directions of IWs. The experimental results indicate that our data set is helpful to better detect IWs, and proposed network can accurately detect IWs in SAR images under various conditions. [ABSTRACT FROM AUTHOR]

A devastating tsunami struck Palu Bay in the wake of the 28 September 2018 Mw = 7.5 Palu earthquake (Sulawesi, Indonesia). With a predominantly strike‐slip mechanism, the question remains whether this unexpected tsunami was generated by the earthquake itself, or rather by earthquake‐induced landslides. In this study we examine the tsunami potential of the co‐seismic deformation. To this end, we present a novel geodetic data set of Global Positioning System and multiple Synthetic Aperture Radar‐derived displacement fields to estimate a 3D co‐seismic surface deformation field. The data reveal a number of fault bends, conforming to our interpretation of the tectonic setting as a transtensional basin. Using a Bayesian framework, we provide robust finite fault solutions of the co‐seismic slip distribution, incorporating several scenarios of tectonically feasible fault orientations below the bay. These finite fault scenarios involve large co‐seismic uplift (>2 m) below the bay due to thrusting on a restraining fault bend that connects the offshore continuation of two parallel onshore fault segments. With the co‐seismic displacement estimates as input we simulate a number of tsunami cases. For most locations for which video‐derived tsunami waveforms are available our models provide a qualitative fit to leading wave arrival times and polarity. The modeled tsunamis explain most of the observed runup. We conclude that co‐seismic deformation was the main driver behind the tsunami that followed the Palu earthquake. Our unique geodetic data set constrains vertical motions of the sea floor, and sheds new light on the tsunamigenesis of strike‐slip faults in transtensional basins. Plain Language Summary: The 28 September Palu earthquake ruptured the Palu‐Koro fault in NW Sulawesi, Indonesia, and was followed by a devastating tsunami in Palu Bay. As the Palu‐Koro fault accommodates mostly horizontal motion, many studies proposed that sub‐marine landslides, rather than the earthquake itself, triggered the tsunami. This study focuses on the contribution of the earthquake to sea floor displacements. We present a unique geodetic data set and estimate a high‐resolution 3D displacement field. The rupture is not a straight feature in the landscape, but rather contains bends. It is near those bends that significant vertical displacements occurred. From the onshore geodetic data we infer another fault bend below Palu Bay. Estimations of fault slip for several scenarios of offshore fault geometries point to a few meters of sea floor uplift. We use these slip models as input for tsunami models, and can qualitatively explain the observations of tsunami runup heights and video‐based tsunami arrival times around Palu Bay. Only at a few locations our models cannot explain tsunami observations, which leaves open the contribution of other possible sources to the tsunami locally. The Palu case underlines the potential importance of fault bends to tsunami generation for similar tectonic settings around the world. Key Points: New Global Positioning System observations as part of a geodetic solution for the full 3D onshore co‐seismic displacements of the 2018 Palu earthquakeBelow Palu Bay we find a strong indication of dip‐slip on a fault bend, agreeing with the notion of Palu Valley being a transtensional basinA large part of the tsunami, both in terms of arrival times and runup heights, can be explained by co‐seismic slip [ABSTRACT FROM AUTHOR]