Range Resolution Research Articles

A tool for estimating ground-based InSAR acquisition characteristics prior to monitoring installation and survey and its differences from satellite InSAR

Abstract. Synthetic Aperture Radar (SAR) acquisition can be performed from satellites or from the ground by means of a so-called GB-InSAR (Ground-Based Interferometry SAR), but the signal emission and the output image geometry slightly differ between the two acquisition modes. Those differences are rarely mentioned in the literature. This paper proposes to compare satellite and GB-InSAR in terms of (1) acquisition characteristics and parameters to consider; (2) SAR image resolution; and (3) geometric distortions that are foreshortening, layover, and shadowing. If in the case of satellite SAR, the range and azimuth resolutions are known and constant along the orbit path, in the case of GB-InSAR their values are terrain-dependent. It is worth estimating the results of a GB-InSAR acquisition that one can expect in terms of range and azimuth resolution, line of sight (LoS) distance, and geometric distortions to select the best installation location when several are possible. We developed a novel tool which estimates those parameters from a digital elevation model (DEM), knowing the GB-InSAR and the slope of interest (SoI) coordinates. This tool, written in MATLAB, was tested on a simple synthetic point cloud representing a cliff with a progressive slope angle to highlight the influence of the SoI geometry on the acquisition characteristics and on two real cases of cliffs located in Switzerland, namely one in the Ticino canton and one in the Vaud canton.

Enhancing autonomous vehicle navigation using SVM-based multi-target detection with photonic radar in complex traffic scenarios

Efficient transportation systems are essential for the development of smart cities. Autonomous vehicles and Intelligent Transportation Systems (ITS) are crucial components of such systems, contributing to safe, reliable, and sustainable transportation. They can reduce traffic congestion, improve traffic flow, and enhance road safety, thereby making urban transportation more efficient and environmentally friendly. We present an innovative combination of photonic radar technology and Support Vector Machine classification, aimed at improving multi-target detection in complex traffic scenarios. Central to our approach is the Frequency-Modulated Continuous-Wave photonic radar, augmented with spatial multiplexing, enabling the identification of multiple targets in various environmental conditions, including challenging weather. Notably, our system achieves an impressive range resolution of 7 cm, even under adverse weather conditions, utilizing an operating bandwidth of 4 GHz. This feature is particularly crucial for precise detection and classification in dynamic traffic environments. The radar system's low power requirement and compact design enhance its suitability for deployment in autonomous vehicles. Through comprehensive numerical simulations, our system demonstrated its capability to accurately detect targets at varying distances and movement states, achieving classification accuracies of 75% for stationary and 33% for moving targets. This research substantially contributes to ITS by offering a sophisticated solution for obstacle detection and classification, thereby improving the safety and efficiency of autonomous vehicles navigating through urban environments.

Protocol and preregistration for the CODEC project: measuring, modelling and mechanistically understanding the nature of cognitive variability in early childhood

BackgroundChildren’s cognitive performance fluctuates across multiple timescales. However, fluctuations have often been neglected in favour of research into average cognitive performance, limiting the unique insights into cognitive abilities and development that cognitive variability may afford. Preliminary evidence suggests that greater variability is associated with increased symptoms of neurodevelopmental disorders, and differences in behavioural and neural functioning. The relative dearth of empirical work on variability, historically limited due to a lack of suitable data and quantitative methodology, has left crucial questions unanswered, which the CODEC (COgnitive Dynamics in Early Childhood) study aims to address.MethodThe CODEC cohort is an accelerated 3-year longitudinal study which encompasses 600 7-to-10-year-old children. Each year includes a ‘burst’ week (3 times per day, 5 days per week) of cognitive measurements on five cognitive domains (reasoning, working memory, processing speed, vocabulary, exploration), conducted both in classrooms and at home through experience sampling assessments. We also measure academic outcomes and external factors hypothesised to predict cognitive variability, including sleep, mood, motivation and background noise. A subset of 200 children (CODEC-MRI) are invited for two deep phenotyping sessions (in year 1 and year 3 of the study), including structural and functional magnetic resonance imaging, eye-tracking, parental measurements and questionnaire-based demographic and psychosocial measures. We will quantify developmental differences and changes in variability using Dynamic Structural Equation Modelling, allowing us to simultaneously capture variability and the multilevel structure of trials nested in sessions, days, children and classrooms.DiscussionCODEC’s unique design allows us to measure variability across a range of different cognitive domains, ages, and temporal resolutions. The deep-phenotyping arm allows us to test hypotheses concerning variability, including the role of mind wandering, strategy exploration, mood, sleep, and brain structure. Due to CODEC’s longitudinal nature, we are able to quantify which measures of variability at baseline predict long-term outcomes. In summary, the CODEC study is a unique longitudinal study combining experience sampling, an accelerated longitudinal ‘burst’ design, deep phenotyping, and cutting-edge statistical methodologies to better understand the nature, causes, and consequences of cognitive variability in children.Trial registrationClinicalTrials.gov - NCT06330090

Protein analysis by desorption electrospray ionization mass spectrometry.

This review presents progress made in the ambient analysis of proteins, in particular by desorption electrospray ionization-mass spectrometry (DESI-MS). Related ambient ionization techniques are discussed in comparison to DESI-MS only to illustrate the larger context of protein analysis by ambient ionization mass spectrometry. The review describes early and current approaches for the analysis of undigested proteins, native proteins, tryptic digests, and indirect protein determination through reporter molecules. Applications to mass spectrometry imaging for protein spatial distributions, the identification of posttranslational modifications, determination of binding stoichiometries, and enzymatic transformations are discussed. The analytical capabilities of other ambient ionization techniques such as LESA and nano-DESI currently exceed those of DESI-MS for in situ surface sampling of intact proteins from tissues. This review shows, however, that despite its many limitations, DESI-MS is making valuable contributions to protein analysis. The challenges in sensitivity, spatial resolution, and mass range are surmountable obstacles and further development and improvements to DESI-MS is justified.

Parallel indirect time-of-flight ranging using on-chip dual-frequency combs

The significant advancements in autonomous vehicle applications demand detection solutions capable of swiftly recognizing and classifying objects amidst rapidly changing and low-visibility conditions. Light detection and ranging (LiDAR) has emerged as a robust solution, overcoming challenges associated with camera imaging, particularly in adverse weather conditions or low illumination. Rapid object recognition is crucial in dynamic environments, but the speed of conventional LiDARs is often constrained by the 2D scanning of the laser beam across the entire scene. In this study, we introduce a parallelization approach for the indirect time-of-flight (iToF) ranging technique. This method enables efficient and high-speed formation of 1D clouds, offering the potential to have extended range capabilities without being constrained by the laser coherence length. The application potential spans mid-range autonomous vehicles ranging to high-resolution imaging. It utilizes dual-frequency combs with slightly different repetition rates. The method leverages the topology of the target object to influence the phase of the beating signal between the comb lines in the RF domain. This approach enables parallel ranging in one direction, confining the scanning process to a single dimension, and offers the potential for high-speed LiDAR systems. A tri-comb approach will be discussed that can provide an extended unambiguous range without compromising the resolution due to the range–resolution trade-off in iToF techniques. The study starts by explaining the technique for parallel detection of distance and velocity. It then presents a theoretical estimation of phase noise for dual combs, followed by an analysis of distance and velocity detection limits, illustrating their maximum and minimum extents. Finally, a study on the mutual interference conditions between two similar LiDAR systems is presented, demonstrating the feasibility of designing simultaneously operating LiDARs to avoid mutual interference.

Broadband super-resolution wavelength-controlled zoom metalens

A design method is proposed for a broadband super-resolution wavelength-controlled zoom metalens with simultaneous modulation of phase, dispersion, and amplitude, and on the basis of enhancing the axial zoom capability of the metalens, the point spread function of the metalens is continuously compressed using the hierarchical direct binary search algorithm, so that the full width at half maximum of the metalens is continuously close to or even less than the diffraction limit of 0.5λ/NA (NA is the numerical aperture). As a theoretical verification, a super-resolution wavelength-controlled zoom metalens was designed operating in the wavelength range of 68–80 μm. The simulation results show that its axial zoom capability is about 1.65 times that of the conventional diffractive metalens, and the lateral resolution in the wavelength range of 68–80 μm is less than the diffraction limit.

4D Single-particle tracking with asynchronous read-out single-photon avalanche diode array detector

Single-particle tracking techniques enable investigation of the complex functions and interactions of individual particles in biological environments. Many such techniques exist, each demonstrating trade-offs between spatiotemporal resolution, spatial and temporal range, technical complexity, and information content. To mitigate these trade-offs, we enhanced a confocal laser scanning microscope with an asynchronous read-out single-photon avalanche diode array detector. This detector provides an image of the particle’s emission, precisely reflecting its position within the excitation volume. This localization is utilized in a real-time feedback system to drive the microscope scanning mechanism and ensure the particle remains centered inside the excitation volume. As each pixel is an independent single-photon detector, single-particle tracking is combined with fluorescence lifetime measurement. Our system achieves 40 nm lateral and 60 nm axial localization precision with 100 photons and sub-millisecond temporal sampling for real-time tracking. Offline tracking can refine this precision to the microsecond scale. We validated the system’s spatiotemporal resolution by tracking fluorescent beads with diffusion coefficients up to 10 μm2/s. Additionally, we investigated the movement of lysosomes in living SK-N-BE cells and measured the fluorescence lifetime of the marker expressed on a membrane protein. We expect that this implementation will open other correlative imaging and tracking studies.

Peering into cloud physics using ultra-fine resolution radar and lidar systems

Abstract Cloud microphysical processes, such as droplet activation, condensational growth, and collisional growth, play a central role in the evolution of clouds and precipitation. Accurate representations of these processes in numerical models are challenging partially due to incomplete understanding of them at the process-level arising from limited systematic observations. Most surface-based active remote sensors, including today’s operational cloud radars and lidars, have a resolution on the order of tens of meters. This resolution is insufficient to resolve cloud microphysical processes that manifest at finer (meter and sub-meter) scales. A new set of ultra-high-resolution ground-based radar and lidar systems have been developed to address this observational gap. The newly developed 94-GHz cloud radar has a range resolution down to 2.8 m, or a factor of 10 finer than typical radars, using a large bandwidth and quadratic phase coding techniques. The lidar has a range resolution down to 10 cm, or a factor of 100 finer than typical lidars, using a time-gated time-correlated single photon counting technique. Such high-resolution observations were previously only achievable through in situ aircraft measurements. Even then, aircraft measurements do not permit continuous long-term cloud observation as is possible with ground-based remote sensing instruments. In this study, the first-light cloud observations from the new radar and lidar systems are shown to reveal detailed cloud structures that conventional sensors could only perceive in a bulk sense, thus providing new avenues to investigate cloud microphysical processes and their impact on weather and climate.

High‐Precision Materials Printer for Fast Prototyping of Electronic Devices Based on 2D Materials

AbstractThere is an increasing interest in printed electronics driven principally by flexible and wearable applications. The interest stems from the ability to fabricate electronic devices, such as Field Effect Transistors (FET), more efficiently in terms of materials use and cost‐effectively than traditional lithographic techniques. Challenges persist in achieving high resolution and accuracy in defining device geometry. In the study, a high‐resolution materials printer able to achieve resolutions in the micron range, surpassing the capabilities of commercially available printers is successfully designed and fabricated. The printer incorporates an all‐in‐one printing system, comprising Inkjet and a Dip Pen Nanolithography (DPN) technique, enabling both additive and subtractive manufacturing at the microscale. The experiments demonstrate the successful fabrication of FETs based on 2D materials (2DMs), with micrometric channel lengths exhibiting a high degree of controllability and repeatability, even when contacting limited channel regions as micrometer‐sized molybdenum disulfide (MoS2) flakes. Electrical characterizations of the fabricated devices underscore the significant technological advancements achieved by the prototypes.

5G Radiation Source Location Based on Passive Virtual Aperture Technology by Single-Satellite

With the development of 5th-Generation Mobile Communication (5G) technology and the deployment of low-Earth orbit satellites, using satellites to locate 5G radiation sources is of great significance in commerce and the military as an important task of integrated sensing and communication. Recently, passive virtual aperture technology has been introduced into passive location to improve accuracy, but the existing method, using matched filters to search the Doppler information to realize the location, has the disadvantages of high complexity and poor range resolution. In this paper, an improved 5G radiation source location based on a virtual aperture is proposed, which uses the improved Golden Section search-fractional Fourier algorithm (GSS-FRFT) to improve the existing passive virtual aperture location methods. First, the received signals are coherently accumulated to convert the time gain into spatial gain, and the subcarrier phase information is extracted by Fast Fourier Transform based on the 5G signal characteristics to obtain the azimuth signal. Then, an improved high-order GSS-FRFT algorithm is proposed to analyze the Doppler information, and signal focusing and satellite ephemeris data are used to estimate the effective velocity and solve the radiation source location. The simulation results show that the proposed method can improve the location accuracy compared with other single-satellite location methods and has high resolution, high accuracy and low complexity compared with the existing passive virtual aperture location method.

Event Vision-based Corner Detection with Count-normalized Multi-Layer Perceptron and Throughput Indicator

The advancement of event cameras has sparked a revolution in imaging technology, presenting exciting opportunities for vision-based measurement tasks. Event cameras operate on an innovative asynchronous imaging principle, which offers several advantages over traditional cameras, including ultra-high dynamic range and exceptional temporal resolution. As a result, event cameras excel in challenging environments characterized by motion blur, overexposure, or underexposure, outperforming conventional frame-based cameras. However, the asynchronous signal streams generated by event cameras pose compatibility challenges with existing vision-based measurement algorithms. This paper focuses specifically on corner detection, a critical vision-based measurement task, tailored for event cameras. To address this challenge, we propose novel corner detectors that leverage advanced optimization techniques, including enhanced time surface representations, multi-layer perceptron classifiers, and an innovative throughput mechanism. Through rigorous experimentation, our method consistently shows lower projection errors compared to state-of-the-art methods across all datasets while also maintaining longer tracking times in low-textured scenarios. Specifically, our CMLP and CMLP-T methods achieve an average valid tracking rate of 83.38% and 84.65%, respectively, on the DAVIS240C dataset collection, surpassing all existing methods. We validate the effectiveness of our proposed corner detectors by demonstrating their enhanced performance compared to state-of-the-art methods. Furthermore, our work contributes to the application of machine learning in event signal processing for vision-based measurement tasks, providing insights into optimizing models for the unique characteristics of event cameras.

Photonic-assisted W-band flexible integrated sensing and communication system for fiber-wireless network based on CE-LFM-OFDM.

We have experimentally demonstrated a constant envelope linear frequency modulated orthogonal frequency division multiplexing (CE-LFM-OFDM) signal by employing an orthogonal frequency division multiplexing (OFDM) signal to phase modulate the linear frequency modulation (LFM) carrier. The experimental verification was conducted in the photonic-based integrated sensing and communication (ISAC) system working at 94.5 GHz. In our system, a 10-km optical fiber and a 1-m free space transmission are incorporated, achieving seamless fiber-wireless networks. As a result, we achieved data rates ranging from 8 to 15.4 Gbit/s and range resolution ranging from 1.5 to 7.5 cm, respectively.

Rapid-scan broadband frequency-domain terahertz spectroscopy via dynamic optical phase lock

Frequency-domain terahertz (THz) spectroscopy using photomixing devices has unique advantages such as high dynamic range and high spectral resolution. Thus, many applications for solid-state and gas-phase spectroscopy have been proposed. In this study, we developed a feedback controlled technique to dynamically compensate for the optical phase accompanied by frequency sweep, enabling both fast and high-resolution data acquisition across a wide frequency region. From gas-phase THz spectroscopy measurements of dilute acetonitrile gas in a wide frequency range up to 1.1 THz, fine structures with linewidths less than 10 MHz were clearly resolved, while the data acquisition rate was improved by two orders compared to the previously reported value.

Inverted flap technique versus internal limiting membrane insertion for macular hole in eyes with extremely high myopia

BackgroundTo compare the surgical outcomes of the inverted internal limiting membrane (ILM) flap technique and ILM insertion for macular hole (MH) without retinal detachment in eyes with extremely high myopia.MethodsIn this retrospective study, we analyzed 22 eyes with an axial length ≥ 30.0 mm that had underwent MH surgery between April 2015 and August 2021. The surgical procedures involved either an inverted ILM flap or ILM insertion. The outcomes were compared between the two techniques. Closure of the MH was confirmed by optical coherence tomography (OCT). The best-corrected visual acuity (BCVA) was measured before and after surgery. Associated complications were documented.ResultsThe median of axial length was 30.64 mm (range, 30.0-34.42). The MH closed in 100% (22/22) eyes and did not recur with a median follow-up of 12.5 months. For the inverted ILM flap technique, the median BCVA improved significantly from 0.80 logarithm of the minimum angle of resolution (logMAR) (range, 0.40-2.00) before surgery to 0.70 logMAR (range, 0.09–1.52) after surgery (p = 0.002). In addition, the median of final BCVA was better for the inverted ILM flap than ILM insertion (0.7 logMAR V.S. 1.00 logMAR; p = 0.016).ConclusionsIn eyes with extremely high myopia, despite comparable effects on MH closure for both ILM insertion and the inverted ILM flap, the later technique achieved significantly better visual outcomes.

GOLEM: Automated and Robust Cryo-EM-Guided Ligand Docking with Explicit Water Molecules.

A detailed understanding of ligand-protein interaction is essential for developing rational drug-design strategies. In recent years, technological advances in cryo-electron microscopy (cryo-EM) brought a new era to the structural determination of biological macromolecules and assemblies at high resolution, marking cryo-EM as a promising tool for studying ligand-protein interactions. However, even in high-resolution cryo-EM results, the densities for the bound small-molecule ligands are often of lower quality due to their relatively dynamic and flexible nature, frustrating their accurate coordinate assignment. To address the challenge of ligand modeling in cryo-EM maps, here we report the development of GOLEM (Genetic Optimization of Ligands in Experimental Maps), an automated and robust ligand docking method that predicts a ligand's pose and conformation in cryo-EM maps. GOLEM employs a Lamarckian genetic algorithm to perform a hybrid global/local search for exploring the ligand's conformational, orientational, and positional space. As an important feature, GOLEM explicitly considers water molecules and places them at optimal positions and orientations. GOLEM takes into account both molecular energetics and the correlation with the cryo-EM maps in its scoring function to optimally place the ligand. We have validated GOLEM against multiple cryo-EM structures with a wide range of map resolutions and ligand types, returning ligand poses in excellent agreement with the densities. As a VMD plugin, GOLEM is free of charge and accessible to the community. With these features, GOLEM will provide a valuable tool for ligand modeling in cryo-EM efforts toward drug discovery.

Exploring a nanostructured X-ray optical device for improved spatial resolution in laboratory X-ray diffraction imaging

Analytical methods with wide field range and high spatial resolution are required to observe the distribution of the crystal structure in micro-regions undergoing macroscopic chemical reactions. A recent X-ray diffraction (XRD) imaging method combines XRD with an X-ray optical device such as a glass polycapillary consisting of a bundle of numerous monocapillaries. The former provides the crystal structure, while the latter controls the shape of the incident or diffracted X-rays and retains the positional information of the sample. Although reducing the monocapillary pore size should improve the spatial resolution, manufacturing technology challenges must be overcome. Here, an anodic aluminium oxide (AAO) film, which forms self-ordered porous nanostructures by anodic oxidation in an electrolyte, is applied as an X-ray optical device. The AAO film (pore diameter: 110 nm; size of the disc: 11 mm; and thickness: 620 µm) was fabricated by anodization in a mixture of oxalic acid and ethylene glycol. The film was incorporated into a laboratory XRD instrument. Compared with using a glass polycapillary alone, using a combination of a glass polycapillary and the AAO film improved the spatial resolution of the XRD imaging method by 40%. This XRD imaging method should not only provide practical analysis in a laboratory environment but also support various observations of the crystal structure distribution.

Increasing the water level accuracy in hydraulic river simulation by adapting mesh level elevation

2D hydraulic models are one of the tools to simulate water levels for effective river management. Mesh resolution in 2D models directly impacts the discretization of the bathymetry, the discharge capacity, and consequently, the accuracy of simulated water levels. The objective of this study is to develop a modified mesh setup that corresponds with the cross-sectional flow volume of the measured cross-section but with a low resolution for the entire discharge range. An algorithm is developed to vertically adjust mesh nodes within a limited range to achieve this objective. Subsequently, the D-Flow-FM software is utilized to model four hypothetical 100-kilometer river reaches to evaluate the modified mesh setup. The findings reveal that the water level using the modified low-resolution mesh is up to 90% closer to the high resolution mesh compared to the original low-resolution mesh for all discharges. Additionally, the simulation of the low-resolution mesh runs approximately 12.5 times faster than their high-resolution counterparts.

Recent Advances in Bio-Inspired Vision Sensor: A Review

Event-based cameras, also known as biologically inspired visual sensors, are capable of capturing real-time scene changes efficiently. Unlike traditional frame-based cameras, event cameras solely report triggered pixel-level brightness changes which are referred to as events. Event-based cameras show many advantages such as high temporal resolution, low latency, and high dynamic range, making them very attractive in robotics and computer vision, especially in challenging scenarios that are too demanding for traditional cameras. In this paper, we provide a comprehensive overview of the emerging field of event-based vision, focusing on the operation principle, sampling mechanisms, and algorithms that take advantage of their superior features. We also delve into the various tasks for which event cameras are utilized, such as object tracking, optical flow estimation, 3D reconstruction, SLAM, image reconstruction, and recognition. Additionally, we highlight the challenges and future opportunities for event cameras, seeking a more efficient way for machines to perceive and interact with the world.

Time-resolved crystallography of boric acid binding to the active site serine of the β-lactamase CTX-M-14 and subsequent 1,2-diol esterification

The emergence and spread of antibiotic resistance represent a growing threat to public health. Of particular concern is the appearance of β-lactamases, which are capable to hydrolyze and inactivate the most important class of antibiotics, the β-lactams. Effective β-lactamase inhibitors and mechanistic insights into their action are central in overcoming this type of resistance, and in this context boronate-based β-lactamase inhibitors were just recently approved to treat multidrug-resistant bacteria. Using boric acid as a simplified inhibitor model, time-resolved serial crystallography was employed to obtain mechanistic insights into binding to the active site serine of β-lactamase CTX-M-14, identifying a reaction time frame of 80–100 ms. In a next step, the subsequent 1,2-diol boric ester formation with glycerol in the active site was monitored proceeding in a time frame of 100–150 ms. Furthermore, the displacement of the crucial anion in the active site of the β-lactamase was verified as an essential part of the binding mechanism of substrates and inhibitors. In total, 22 datasets of β-lactamase intermediate complexes with high spatial resolution of 1.40–2.04 Å and high temporal resolution range of 50–10,000 ms were obtained, allowing a detailed analysis of the studied processes. Mechanistic details captured here contribute to the understanding of molecular processes and their time frames in enzymatic reactions. Moreover, we could demonstrate that time-resolved crystallography can serve as an additional tool for identifying and investigating enzymatic reactions.

Вимоги до вибору значень параметрів радарів із синтезованою апертурою на базі малих космічних апаратів дистанційного зондування Землі

Present-day small satellites for Earth remote sensing have found wide practical application in solving different problems in the socio-economic and defense areas. The use of small satellites is justified as a basis for the formation both of large constellations and constellations of several spacecraft or single spacecraft with the aim to reduce the cost of Earth remote sensing information. The miniaturization of electron components and the latest technological advances have made radar systems compatible with small satellites. The goal of this paper is to present, based on small satellites, expressions for calculating the key parameters of radar systems and their analysis and to calculate possible values of the parameters considered. Possibilities in principle of using synthetic aperture radars (SARs) are considered. The paper presents an overview of Internet sources that give broad information on the recent trends, technologies, and use SAR-equipped satellites. Particular attention is paid to the development of mini- and microspacecraft with X-band SARs operating, in particular, in the stripmap and spotlight modes. The key parameters that have an effect on the SAR possibility of producing high-quality images are presented. By the example of the ICEYE constellation of small satellites, important technical characteristics and parameters of modern radar systems equipped with an active phased array antenna are presented. A model of SAR imaging in the stripmap mode is considered. In the approximation of a rectangular antenna aperture, expressions are given to estimate the slant and the horizontal range resolution and the azimuthal resolution. The available range of the small-satellite SAR pulse repetition frequency is estimated. Relationships between the maximum swath width and the minimum SAR pulse repetition frequency are presented. Expressions are given to estimate the antenna dimensions, the SAR sensitivity, and the signal-to-noise ratio. The presented expressions allow one to analyze the effect of the main technical characteristics and parameters of minisatellite SARs on the design and power characteristics of small satellites and the orbit parameters. The obtained results make it possible to develop recommendations on the design of imaging equipment for home low-orbit satellites and their constellations.