Progressive Scan Research Articles

A Radio Frequency Interference Screening Framework—From Quick-Look Detection Using Statistics-Assisted Network to Raw Echo Tracing

Synthetic aperture radar (SAR) is often affected by other high-power electromagnetic devices during ground observation, which causes unintentional radio frequency interference (RFI) with the acquired echo, bringing adverse effects into data processing and image interpretation. When faced with the task of screening massive SAR data, there is an urgent need for the global perception and detection of interference. The existing RFI detection method usually only uses a single type of data for detection, ignoring the information association between the data at all levels of the real SAR product, resulting in some computational redundancy. Meanwhile, current deep learning-based algorithms are often unable to locate the range of RFI coverage in the azimuth direction. Therefore, a novel RFI processing framework from quick-looks to single-look complex (SLC) data and then to raw echo is proposed. We take the data of Sentinel-1 terrain observation with progressive scan (TOPS) mode as an example. By combining the statistics-assisted network with the sliding-window algorithm and the error-tolerant training strategy, it is possible to accurately detect and locate RFI in the quick looks of an SLC product. Then, through the analysis of the TOPSAR imaging principle, the position of the RFI in the SLC image is preliminarily confirmed. The possible distribution of the RFI in the corresponding raw echo is further inferred, which is one of the first attempts to use spaceborne SAR data to ‌elucidate the RFI location mapping relationship between image data and raw echo. Compared with directly detecting all of the SLC data, the time for the proposed framework to determine the RFI distribution in the SLC data can be shortened by 53.526%. All the research in this paper is conducted on Sentinel-1 real data, which verify the feasibility and effectiveness of the proposed framework for radio frequency signals monitoring in advanced spaceborne SAR systems.

Transcobalamin receptor antibodies in autoimmune vitamin B12 central deficiency.

Vitamin B12 is critical for hematopoiesis and myelination. Deficiency can cause neurologic deficits including loss of coordination and cognitive decline. However, diagnosis relies on measurement of vitamin B12 in the blood, which may not accurately reflect the concentration in the brain. Using programmable phage display, we identified an autoantibody targeting the transcobalamin receptor (CD320) in a patient with progressive tremor, ataxia, and scanning speech. Anti-CD320 impaired cellular uptake of cobalamin (B12) in vitro by depleting its target from the cell surface. Despite a normal serum concentration, B12 was nearly undetectable in her cerebrospinal fluid (CSF). Immunosuppressive treatment and high-dose systemic B12 supplementation were associated with increased B12 in the CSF and clinical improvement. Optofluidic screening enabled isolation of a patient-derived monoclonal antibody that impaired B12 transport across an in vitro model of the blood-brain barrier (BBB). Autoantibodies targeting the same epitope of CD320 were identified in seven other patients with neurologic deficits of unknown etiology, 6% of healthy controls, and 21.4% of a cohort of patients with neuropsychiatric lupus. In 132 paired serum and CSF samples, detection of anti-CD320 in the blood predicted B12 deficiency in the brain. However, these individuals did not display any hematologic signs of B12 deficiency despite systemic CD320 impairment. Using a genome-wide CRISPR screen, we found that the low-density lipoprotein receptor serves as an alternative B12 uptake pathway in hematopoietic cells. These findings dissect the tissue specificity of B12 transport and elucidate an autoimmune neurologic condition that may be amenable to immunomodulatory treatment and nutritional supplementation.

Why Violence Cannot be Prevented in Healthcare Settings in Türkiye?: A Retrospective Policy Analysis.

Preventive policies have been devised with the aim of curbing health-related violence, and their efficacy is believed to furnish evidence for their continued implementation, thereby enhancing their effectiveness. This study undertakes a retrospective analysis of these policies in the context of Türkiye. A comprehensive examination involved the review of 26 documents, employing a progressive scanning approach for data collection. This methodology encompassed the utilization of gray literature databases (OECD iLibrary and WHO Iris), extensive Google searches, thorough website scans, and consultations with subject-matter experts. Data analysis was meticulously conducted within the framework of the Health Policy Triangle. The findings reveal active participation from diverse stakeholders, including governmental bodies, political entities, professional organizations, and trade unions, in various preventive initiatives aimed at mitigating health-related violence. Notably, the adoption of legislation for health violence prevention, perceived as a paramount achievement, can be attributed to persistent efforts by both the media and other influential actors and stakeholders. These endeavors have sustained the topic's prominence on the policy agenda, positioning it as a promising source for the development of novel violence prevention and management strategies. This study underscores the necessity for a comprehensive investigation into the working conditions, personal rights, and wage policies of healthcare workers, in light of documented factors that frequently precipitate violence. Concomitantly, it advocates for the development of effective mechanisms to address these issues.

A fast image inpainting algorithm based on an adaptive scanning strategy

OBJECTIVES: In exemplar-based image inpainting algorithms, there are often issues with the calculation of patch similarity for matching, suboptimal strategies for selecting matching patches, and low inpainting speed.METHODS: This paper first uses the variable scale cross-scan block line progressive scan to solve the problem of slow scanning speed and invalid priority formula. Then, an improved weight similarity formula is used for searching to solve the problem of poor computing strategy for similar matching patches. The search range of matching patches gradually increases from small to large until globally searching for similar matching patches to improve the efficiency of inpainting. To further improve the correctness of matching patch selection, this paper uses six levels of priority matching criteria for screening.RESULTS: The experimental results show that the inpainting effect of the proposed method is significantly improved in subjective vision, and the structural similarity (SSIM), peak signal-to-noise ratio (PSNR), and inpainting speed of the inpainting results are all improved.CONCLUSION: For different types of images, the proposed method has a better inpainting effect and higher inpainting speed than the other three advanced methods.

Precise State-of-Charge Mapping via Deep Learning on Ultrasonic Transmission Signals for Lithium-Ion Batteries

The uneven distribution of state of charge (SoC) in the lithium-ion battery is a key factor to cause fast decay of local electrochemical performance. Here, we report an acoustic method to realize SoC mapping in a pouch cell. A focused ultrasound beam is used to scan the cell, and the transmitted ultrasonic wave is analyzed with a deep learning algorithm based on the feedforward neural network. The deep learning algorithm effectively suppresses the disturbance of structural variation in different cells. As a result, the root mean squared error (RMSE) of the estimated local SoC is reduced to 3.02% when applying to different positions on different pouch cells, which is 11.07% of the RMSE by direct fitting SoC with acoustic time of flight. Combining with the progressive scanning technique, our method can realize non-destructive in situ SoC mapping with 1 mm in-plane resolution on pouch cells.

Efficient and precise detection for surface flaws on large-aperture optics based on machine vision and machine learning

Large-aperture optical components have a wide application in high-power laser facilities. Surface flaws such as damages and contaminants generated under high-power laser irradiation can greatly affect the optical or mechanical performance of optics, so the optical components must be carefully inspected to evaluate optics damage and cleanliness. However, it is of great challenge to achieve rapid and accurate positioning, classification, and measurement of micron-level flaws on the surface of large-aperture optics. This paper proposes a novel surface flaw detection technology based on machine vision and machine learning. To balance efficiency and accuracy, a dark-field imaging system based on progressive scanning is designed to obtain the image of optics surface. A set of surface flaw detection algorithms based on machine learning including object segmentation, flaw feature extraction, and classification and size calibration of flaw are proposed to accurately assess the state of surface flaws. The experiments show that the system can complete the detection of an optical component (430 mm × 430 mm) within 6 min. The minimum detectable size of the flaws can reach 20 μm, and the position accuracy of the flaws is better than 50 μm. The classification accuracy of flaw is 98.59 %, and the average relative errors of the size measurement of damages and contaminants are 3.23 % and 6.58 %, respectively. The experimental results demonstrate the effectiveness of the method in detecting surface flaws of large-aperture optics.

The capability of Sentinel-1 polarization combinations for oil spill detection (study case: Karawang, Indonesia)

Marine pollution is one of issues that is widely discussed such as marine debris, chemical contamination, and oil spill. It has many impacts on the environment. Remote sensing helps detect the presence of an oil spill via satellite platform. One commonly used satellite is Synthetic-Aperture Radar (SAR) imagery, which can see oil spills even in cloudy conditions. However, the black and white appearance of the radar sometimes makes it difficult to distinguish between an oil spill and look alike. Therefore, this study aims to determine the polarization combination in the Sentinel-1 SAR imagery. Sentinel-1 Single Look Complex (SLC) is used as input and processes through various stages to obtain Coherence Vertical-Vertical (VV) and Vertical-Horizontal (VH) results. There are four steps for processing the data; convert the data to backscattering coefficient from SLC data, stacking, Terrain Observation by Progressive Scan (TOPS) coherence, and building the robust combinations. The polarization in the Sentinel-1 was calculated to determine artificial bands for the correct combination, namely Divide (VV/VH) as band 1, Average ((VV+VH)/2) as band 2, Multiple (VVxVH) as band 3, Add (VV+VH) as band 4, and Subtract (VV-VH) as band 5. Furthermore, the determination of the band used in the polarization composite display is based on the intensity value. As a result, the recommendation for Sentinel-1 polarization is obtained, which involves bands 2, 3, and 5.

Electrical and Optical Properties of Laser-Induced Structural Modifications in PbSe Films

PbSe chalcogenide films are widely used as photosensitive elements in gas analysis devices. High absorption in the IR spectrum region and low electrical resistance are important characteristics. Continuous laser radiation exposure of films in the near UV range makes it possible to achieve the desired characteristics, replacing oven heat treatment in the technological process. In the considered laser technology, PbSe films are subjected to photothermal action by a spot of focused radiation in the progressive scanning mode. In this work, changes in the optical and electrical film properties were studied, and the mechanism of structural laser modification was also considered.

A Unified Algorithm for the Sliding Spotlight and TOPS Modes Data Processing in Bistatic Configuration of the Geostationary Transmitter with LEO Receivers

This paper deals with the imaging problem for sliding spotlight (SS) and terrain observation by progressive scan (TOPS) modes in bistatic configuration of the geostationary (GEO) transmitter with a low earth orbit satellite (LEO) receiver, named GTLR-BiSAR system. A unified imaging algorithm is proposed to process the GTLR-BiSAR data acquired in SS or TOPS modes. Our main contributions include four aspects. Firstly, the imaging geometry of this novel configuration is described in detail. Furthermore, the GTLR-BiSAR signal expressions were deduced in both time and frequency domains. These signal expressions provide great support for the design of processing the algorithm theoretically. Secondly, we present a unified deramping-based technique according to the special geometry of GTLR-BiSAR to overcome the azimuth spectrum aliasing phenomenon, which typically affects SS and TOPS data. Thirdly, the spatial variance of GTLR-BiSAR data were thoroughly analyzed based on the range-Doppler (RD) geolocation functions. On the basis of a former analysis, we put forward the azimuth variance correction strategy and modified the conventional chirp scaling function to solve the range variance problem. Finally, we completed the derivation of the two-dimensional spectrum after the range chirp scaling. On the basis of spectrum expressions, we compensated for the quadratic and residue phase, and the azimuth compression was completed by SPECAN operation. In addition, we provide a flow diagram to visually exhibit the processing procedures. At the end of this paper, the simulation and real data experiment results are presented to validate the effectiveness of the proposed algorithm.

A Deep Learning Based Super Resolution DoA Estimator With Single Snapshot MIMO Radar Data

In this article, we study the radar angular resolution, the capability of distinguishing multiple targets in different directions of arrivals (DoA). We present a deep learning-based super resolution DoA estimator for multiple input multiple output (MIMO) radar with single snapshot data. The estimator consists of a deep learning DoA classifier (DLDC) in the central bearing angle zone, which can simultaneously detect up to 11 targets in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$[ { - 2^\circ,\ 2^\circ } ]$</tex-math></inline-formula> with 32 virtual antenna elements, and a spatial filtering pre-rotator (SFPR) that makes the DLDC supporting any bearing angle location in a wider radar field of view (FoV). We present the DLDC-SFPR structure and provide detailed parameter setting. In the performance evaluation, the resolution of proposed method is first compared with the theoretical angular resolution limit (ARL). It is shown that the proposed estimator reaches the Chernoff ARL. The probability of resolution (PoR) is then investigated and compared with typical and state-of-the-art DoA estimators in various conditions. The numerical results show that the DLDC-SFPR achieves 0.4 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">°</sup> resolution with 90% PoR to distinguish 2 targets at signal to noise ratio (SNR) of 7 dB if the targets are on-gird. In the case of any-angle, the same resolution and probability are achieved at SNR = 12 dB. The proposed method is robust to multi-target concurrent cases, and outperforms the existing reported approaches. Two procedures, uniform scanning and progressive scanning, are proposed for wider FoV applications.

Analysis and quality of biomedical images

The analysis of biomedical images is carried out. Analytical expressions to determine the quantum efficiency of the visual analyzer are obtained. The relationship between the capabilities of the visual analyzer and the quality of the original image is determined. The calculation of the eye sensitivity to television noise and its numerical analysis are carried out. It is established that the gain coefficient of iridological television systems should be sufficient to eliminate losses in the visual analyzer associated with its low quantum efficiency. Keywords iridological, scan, television camera, progressive scan, interlaced scan, circular scan, radial scan, triangular scan, tracking scan

PS-ESD: Persistent Scatterer-Based Enhanced Spectral Diversity Approach for Time-Series Sentinel-1 TOPS Data Co-Registration

In Sentinel-1 terrain observation with progressive scan (TOPS) mode, this azimuth sweeping introduces an extra high-frequency Doppler term into the impulse response function, which requires the azimuth co-registration accuracy of 0.001 pixels to make the interferometric phase difference of adjacent bursts less than 3&#x00B0;. The enhanced spectral diversity (ESD) and developing versions are usually used to correct such residual azimuth misregistration. However, in fast decorrelation scenario, the distributed scatterers (DSs)-based ESDs need to perform lots of complex data processing to reduce the decorrelation impact on high-precision co-registration, including multilooking, spatial filtering, network construction, and least square adjustment. The DS-based co-registration methods are complicated and inefficient, which is not suitable for big SAR data processing. Therefore, this paper proposes a persistent scatterers-based ESD (PS-ESD): to estimate the amplitude dispersion index (ADI) with double samples over the burst overlap regions and select the satisfied PS pixels to compute the double differential phase under the one-master interferometric framework for correcting the time-series azimuth shifts. Based on the Sentinel-1 TOPS SAR data over the mountainous area in Three Gorges, China, experimental results have demonstrated that the proposed PS-ESD can achieve higher co-registration accuracy and faster convergence rate, especially in the case of dynamic co-registration of newly added TOPS images.

Wavelets and digital filters designed and synthesized in the time and frequency domains.

The relevance of the problem under study is due to the fact that the comparison is made for wavelets constructed in the time and frequency domains. The wavelets constructed in the time domain include all discrete wavelets, as well as continuous wavelets based on derivatives of the Gaussian function. This article discusses the possibility of implementing algorithms for multiscale analysis of one-dimensional and two-dimensional signals with the above-mentioned wavelets and wavelets constructed in the frequency domain. In contrast to the discrete wavelet transform (Mallat algorithm), the authors propose a multiscale analysis of images with a multiplicity of less than two in the frequency domain, that is, the scale change factor is less than 2. Despite the fact that the multiplicity of the analysis is less than 2, the signal can be represented as successive approximations, as with the use of discrete wavelet transform. Reducing the multiplicity allows you to increase the depth of decomposition, thereby increasing the accuracy of signal analysis and synthesis. At the same time, the number of decomposition levels is an order of magnitude higher compared to traditional multi-scale analysis, which is achieved by progressive scanning of the image, that is, the image is processed not by rows and columns, but by progressive scanning as a whole. The use of the fast Fourier transform reduces the conversion time by four orders of magnitude compared to direct numerical integration, and due to this, the decomposition and reconstruction time does not increase compared to the time of multiscale analysis using discrete wavelets.

Mechanism of Cavitation Wear of a Low-Friction Composite Coating CrN+WC/C Deposed on Ferritic-Pearlitic P265GH and Austenitic X2CrNi18-9 (304L) Steels

In order to meet the expectations of the global industry in areas such as: energy, heating, aviation, automotive, railway, chemical, petrochemical, oil, gas, river and marine sectors, where material wear processes may occur due to the flow of water gas and steam or their mixtures with various degree of saturation at different pressures, the authors of this article have conducted research on the resistance to cavitation wear of a low-friction composite anti-wear PVD coating in the form of chromium nitride and tungsten carbide (CrN+WC/C) deposited by a physical method on the surface of structural elements in the form of cavitation generators operating in extreme conditions of cavitation wear. Structural elements were examined made of steel with the ferritic-perlitic structure of the P265GH grade and with the austenitic chromium-nickel structure of the X2CrNi18-9 (304L) grade with a protective composite low-friction coating applied onto their surfaces by the Physical Vapour Deposition (PVD) technique, intended for operation in the cavitation wear environment. In order to obtain the results, the investigations of mass loss and roughness profile changes were conducted and the analysis of structural-metallographic morphology changes on the surfaces of structural elements was performed using a scanning electron microscope at voltages accelerating from 5 to 20kV using secondary electrons detection. The results of cavitation wear on the surface of structural elements were obtained using a digital microscope operating in 4K technology with a progressive scanning system.

High Speed Maneuvering Platform Squint TOPS SAR Imaging Based on Local Polar Coordinate and Angular Division

This paper proposes an imaging algorithm for synthetic aperture radar (SAR) mounted on a high-speed maneuvering platform with squint terrain observation by progressive scan mode. To overcome the mismatch between range model and the signal after range walk correction, the range history is calculated in local polar format. The Doppler ambiguity is resolved by nonlinear derotation and zero-padding. The recovered signal is divided into several blocks in Doppler according to the angular division. Keystone transform is used to remove the space-variant range cell migration (RCM) components. Thus, the residual RCM terms can be compensated by a unified phase function. Frequency domain perturbation terms are introduced to correct the space-variant Doppler chirp rate term. The focusing parameters are calculated according to the scene center of each angular block and the signal of each block can be processed in parallel. The image of each block is focused in range-Doppler domain. After the geometric correction, the final focused image can be obtained by directly combined the images of all angular blocks. Simulated SAR data has verified the effectiveness of the proposed algorithm.

Interseismic Deformation From Sentinel‐1 Burst‐Overlap Interferometry: Application to the Southern Dead Sea Fault

AbstractInterferometric Synthetic Aperture Radar (InSAR) data are increasingly being used to map interseismic deformation with ascending and descending‐orbit observations allowing for resolving the near‐east and vertical displacement components. The north component has, however, been difficult to retrieve due to the limited sensitivity of standard InSAR observations in that direction. Here, we address this problem by using time‐series analysis of along‐track interferometric observations in burst‐overlap areas of the Terrain Observation with Progressive Scan imaging mode of the Sentinel‐1 radar satellites. We apply this method to the southern part of the near‐north striking Dead Sea transform fault to show that the ∼5 mm/year relative motion is well recovered. Furthermore, the results indicate the locking depth of the fault decreases toward the south as it enters the transtensional Gulf of Aqaba basin. Our results show that time‐series analysis of burst‐overlap interferometric observations can be used to obtain meaningful interseismic deformation rates of slow‐moving and northerly striking faults.

Review on Deinterlacing Algorithms

Interlacing is a commonly used technique for doubling the perceived frame rate without adding bandwidth in television broadcasting and video recording. During playback, however, it exhibits disturbing visual artifacts such as flickering and combing. As a result in modern display devices, video deinterlacing is used where the interlaced video format is converted to progressive scan format to overcome the limitations of interlaced video. This conversion is achieved through interpolating interlaced video. Current deinterlacing approaches either neglect temporal information for real-time performance but poor visual quality, or estimate motion for better deinterlacing but higher computational cost. This paper focuses on surveying the deinterlacing algorithms which apply both spatial and temporal-based methods and focus on different aspects of both motion-adaptive, non-motion adaptive, and the time complexity through these implementations.

Intrapulse Azimuth Frequency Scanning-Based 2-D Scanning SAR for HRWS Imaging

In this article, a novel 2-D scanning synthetic aperture radar mode for high-resolution and wide-swath imaging is introduced. Instead of the interpulse progressive azimuth beam scanning used in Terrain Observation by Progressive Scans (TOPS) mode, the intrapulse continuous azimuth frequency scanning is employed in this mode. The same azimuth resolution as the multichannel TOPS mode can be obtained through this mode in the case of single channel transmitting and receiving. And the wide-swath imaging in range is still achieved through the cyclically elevation beam scanning from burst to burst. Moreover, the antenna aperture can be fully exploited for transmitting in this mode. Therefore, it will outperform the multichannel TOPS mode especially in the case of active array antenna. The signal model of this mode is derived. Based on the analysis of the characteristics of echo spectrum, the design criteria for this mode are developed, followed by a design example. Finally, an imaging algorithm for this mode is presented. Theoretical analysis and numerical simulations verify the effectiveness of the proposed design criteria and imaging algorithm.

Image Inpainting Based on Structural Tensor Edge Intensity Model

In the exemplar-based image inpainting approach, there are usually two major problems: the unreasonable calculation of priority and only considering the color features in the patch lookup strategy. In this paper, we propose an image inpainting approach based on the structural tensor edge intensity model. First, we use the progressive scanning inpainting method to avoid the image filling order being affected by the priority function. Then, we use the edge intensity model to build the patches similarity function for correctly identifying the local image structure. Finally, the balance operator is used to restrict the excessive propagation of structural information to ensure the correct structural reconstruction. The experimental results show that the our approach is comparable and even superior to some state-of-the-art inpainting algorithms.

A Signal Model for PRF Dithering in Wide-Swath, Fine-Resolution InSAR

Wide-swath radar imaging requires that the time interval to collect each radar pulse echo is large and can often exceed the interpulse period. As it is difficult to both transmit and receive from the same antenna simultaneously, there will be “blind ranges” when the receive and transmit times overlap. This leads to gaps in the radar echo and thus degradation of system performance. Today, most wide-swath systems address this by segmenting the swath in range, such as in the ScanSAR or Terrain Observation with Progressive Scan (TOPS) mode operation, so that each subswath is within the range ambiguity limit. Some groups have started experimenting with the variations in the sweepSAR technology, in which the receive antenna tracks the radar echo across the swath, realizing a complete wide-swath range scan but leading to the echo gaps. Here, we look at minimizing the effect of blind ranges by varying the radar pulse-repetition frequency (PRF) and interpolating across the gaps to preserve azimuth signal continuity. If the pulse times are selected properly, the main effect is to raise the noise floor of the echoes. Geocoded magnitude images, interferograms and correlation images, and deformation time series show strong robustness with respect to dithering, demonstrating that choosing essentially random PRFs allows for accurate generation of SAR and Interferometric Synthetic Aperture Radar (InSAR) data products while retaining wide-swath, fine-resolution coverage.