Search NASA⌕ Search

SEARCH · Search NASA

Results for “Sensor spatial resolution”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 685 records · Page 38

Low-symmetry vacancy-related spin qubit in hexagonal boron nitride

Abstract Point defect qubits in semiconductors have demonstrated their outstanding capabilities for high spatial resolution sensing generating broad multidisciplinary interest. Hexagonal boron nitride (hBN) hosting point defect qubits have recently opened up new horizons for quantum sensing by implementing sensing foils. The sensitivity of point defect sensors in hBN is currently limited by the linewidth of the magnetic resonance signal, which is broadened due to strong hyperfine couplings. Here, we report on a vacancy-related spin qubit with an inherently low symmetry configuration, the VB2 center, giving rise to a reduced magnetic resonance linewidth at zero magnetic fields. The VB2 center is also equipped with a classical memory that can be utilized for storing population information. Using scanning transmission electron microscopy imaging, we confirm the existence of the VB2 configuration in free-standing monolayer hBN.

Chemistry↗

Identifications and classifications of human locomotion using Rayleigh-enhanced distributed fiber acoustic sensors with deep neural networks

Abstract This paper reports on the use of machine learning to delineate data harnessed by fiber-optic distributed acoustic sensors (DAS) using fiber with enhanced Rayleigh backscattering to recognize vibration events induced by human locomotion. The DAS used in this work is based on homodyne phase-sensitive optical time-domain reflectometry (φ-OTDR). The signal-to-noise ratio (SNR) of the DAS was enhanced using femtosecond laser-induced artificial Rayleigh scattering centers in single-mode fiber cores. Both supervised and unsupervised machine-learning algorithms were explored to identify people and specific events that produce acoustic signals. Using convolutional deep neural networks, the supervised machine learning scheme achieved over 76.25% accuracy in recognizing human identities. Conversely, the unsupervised machine learning scheme achieved over 77.65% accuracy in recognizing events and human identities through acoustic signals. Through integrated efforts on both sensor device innovation and machine learning data analytics, this paper shows that the DAS technique can be an effective security technology to detect and to identify highly similar acoustic events with high spatial resolution and high accuracies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

28nm front end ASIC and 12” LGADs for 3D integration

The 3DIntSenS Collaboration—a joint effort between SLAC, Fermilab, and LLNL—is developing enabling technologies for next-generation radiation imaging detectors that combine ultra-fine spatial resolution (≈10 μm) with precision timing (<20 ps), while maintaining low power <1 W/cm2 and high data throughput. The approach leverages 3D integration between advanced CMOS readout ASICs and finely pixelated LGAD sensors to achieve the performance and scalability required for large-area, high-rate applications. High-granularity, precision-timing detectors are essential for scientific advances in HEP, NP, BES, and FES, but widespread adoption is limited by the cost and complexity of 3D integration. To close this gap, the collaboration is developing LGAD sensors compatible with 12-inch commercial CMOS processes, enabling cost-effective integration with high-performance ASICs under development. We present the design and results from a 28 nm CMOS ASIC prototype, including a low-jitter front end, and in-pixel TDC demonstrating sub-10 ps timing resolution. We also report on the co-design and characterization of reticle-scale LGAD sensors with 50 μm and 100 μm pixels and introduce the next 10k-pixel ASIC designed for full 3D integration. These advances represent a critical step toward scalable, high-resolution radiation imaging systems for future scientific instrumentation.

England, Troy [Fermilab] (ORCID:0000000154405255)↗

Real time thermal imaging for analysis and control of crystal growth by the Czochralski technique

A real time thermal imaging system with temperature resolution better than +/- 0.5 C and spatial resolution of better than 0.5 mm has been developed. It has been applied to the analysis of melt surface thermal field distributions in both Czochralski and liquid encapsulated Czochralski growth configurations. The sensor can provide single/multiple point thermal information; a multi-pixel averaging algorithm has been developed which permits localized, low noise sensing and display of optical intensity variations at any location in the hot zone as a function of time. Temperature distributions are measured by extraction of data along a user selectable linear pixel array and are simultaneously displayed, as a graphic overlay, on the thermal image.

Wargo, M. J.↗

Initial Performance of the Aspect System on the Chandra Observatory: Post-Facto Aspect Reconstruction

The aspect system of the Chandra Observatory plays a key role in realizing the full potential of Chandra's x-ray optics and detectors. To achieve the highest spatial and spectral resolution (for grating observations), an accurate post-facto time history of the spacecraft attitude and internal alignment is needed. The CXC has developed a suite of tools which process sensor data from the aspect camera assembly and gyroscopes, and produce the spacecraft aspect solution. In this poster, the design of the aspect pipeline software is briefly described, followed by details of aspect system performance during the first eight months of flight. The two key metrics of aspect performance are: image reconstruction accuracy, which measures the x-ray image blurring introduced by aspect; and celestial location, which is the accuracy of detected source positions in absolute sky coordinates.

Aldcroft, T.↗

Comparisons of Arctic In-Situ Snow and Ice Data with Airborne Passive Microwave Measurements

As part of the AMSR-E sea ice validation campaign in March 2003, aircraft flights over the Arctic sea ice were coordinated with ground measurements of snow and sea ice properties. The surface-based measurements were in the vicinity of Barrow, AK, and at a Navy ice camp located in the Beaufort Sea. The NASA P-3 aircraft was equipped with the NOAA ETL PSR microwave radiometer that has the same frequencies as the AMSR-E sensor. The goal was to validate the standard AMSR-E products ice temperature and snow depth on sea ice. Ground measurements are the only way to validate these parameters. The higher spatial resolution of the PSR instrument (between 30 and 500 m, depending on altitude) enables a better comparison between ground measurements and microwave data because of the expected smaller spatial variability. Maps of PSR data can then be used for further down-scaling to AMSR-E pixel areas. Initial results show a good qualitative agreement between the in-situ snow depths and the PSR data. Detailed studies are underway and latest results will be presented.

Markus, T.↗

NASA's New Laser Risk Reduction Program For Future Space Lidar Missions

NASA has been performing ground, airborne, and space-based scientific measurements since it was formed in 1958. Initial ground and airborne measurements were made with in situ instruments. By necessity, initial earth observation space-based missions were accomplished with passive remote sensing. Active microwave radar was added to the sensor repertoire in the late 1970s. A few key measurements important to NASA remain unaccomplished, however, despite the passive and radar successes. These critical measurements include space-based altimetry; and high spatial resolution profiling of aerosol properties, wind velocity, clouds, and molecular concentrations. Fortunately, a new technology, active optical radar or laser radar or lidar, has matured to the point that the last decade has seen a growing consideration of lidar for space missions. Part of the surge in consideration of lidar has been the tremendous progress in solid-state lasers fueled by advances in crystal growth quality and pump laser diode technology.

Michael J. Kavaya↗

Forest Canopy Cover and Height from MISR in Topographically Complex Southwestern US Landscape Assessed with High Quality Reference Data

This study addresses the retrieval of spatially contiguous canopy cover and height estimates in southwestern USforests via inversion of a geometric-optical (GO) model against surface bidirectional reflectance factor (BRF) estimates from the Multi-angle Imaging SpectroRadiometer (MISR). Model inversion can provide such maps if good estimates of the background bidirectional reflectance distribution function (BRDF) are available. The study area is in the Sierra National Forest in the Sierra Nevada of California. Tree number density, mean crown radius, and fractional cover reference estimates were obtained via analysis of QuickBird 0.6 m spatial resolution panchromatic imagery usingthe CANopy Analysis with Panchromatic Imagery (CANAPI) algorithm, while RH50, RH75 and RH100 (50, 75, and 100 energy return) height data were obtained from the NASA Laser Vegetation Imaging Sensor (LVIS), a full waveform light detection and ranging (lidar) instrument. These canopy parameters were used to drive a modified version of the simple GO model (SGM), accurately reproducing patterns ofMISR 672 nm band surface reflectance (mean RMSE 0.011, mean R2 0.82, N 1048). Cover and height maps were obtained through model inversion against MISR 672 nm reflectance estimates on a 250 m grid.The free parameters were tree number density and mean crown radius. RMSE values with respect to reference data for the cover and height retrievals were 0.05 and 6.65 m, respectively, with of 0.54 and 0.49. MISR can thus provide maps of forest cover and height in areas of topographic variation although refinements are required to improve retrieval precision.

Chopping, Mark↗

The Ocean Colour Climate Change Initiative: II. Spatial and Temporal Homogeneity of Satellite Data Retrieval Due to Systematic Effects in Atmospheric Correction Processors

The established procedure to access the quality of atmospheric correction processors and their underlying algorithms is the comparison of satellite data products with related in-situ measurements. Although this approach addresses the accuracy of derived geophysical properties in a straight forward fashion, it is also limited in its ability to catch systematic sensor and processor dependent behaviour of satellite products along the scan-line, which might impair the usefulness of the data in spatial analyses. The Ocean Colour Climate Change Initiative (OC-CCI) aims to create an ocean colour dataset on a global scale to meet the demands of the ecosystem modelling community. The need for products with increasing spatial and temporal resolution that also show as little systematic and random errors as possible, increases. Due to cloud cover, even temporal means can be influenced by along-scanline artefacts if the observations are not balanced and effects cannot be cancelled out mutually. These effects can arise from a multitude of results which are not easily separated, if at all. Among the sources of artefacts, there are some sensor-specific calibration issues which should lead to similar responses in all processors, as well as processor-specific features which correspond with the individual choices in the algorithms. A set of methods is proposed and applied to MERIS data over two regions of interest in the North Atlantic and the South Pacific Gyre. The normalised water leaving reflectance products of four atmospheric correction processors, which have also been evaluated in match-up analysis, is analysed in order to find and interpret systematic effects across track. These results are summed up with a semi-objective ranking and are used as a complement to the match-up analysis in the decision for the best Atmospheric Correction (AC) processor. Although the need for discussion remains concerning the absolutes by which to judge an AC processor, this example demonstrates clearly, that relying on the match-up analysis alone can lead to misjudgement.

Ocean Colour↗

Spatial Aspects of Multi-Sensor Data Fusion: Aerosol Optical Thickness

The Goddard Earth Sciences Data and Information Services Center (GES DISC) investigated the applicability and limitations of combining multi-sensor data through data fusion, to increase the usefulness of the multitude of NASA remote sensing data sets, and as part of a larger effort to integrate this capability in the GES-DISC Interactive Online Visualization and Analysis Infrastructure (Giovanni). This initial study focused on merging daily mean Aerosol Optical Thickness (AOT), as measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites, to increase spatial coverage and produce complete fields to facilitate comparison with models and station data. The fusion algorithm used the maximum likelihood technique to merge the pixel values where available. The algorithm was applied to two regional AOT subsets (with mostly regular and irregular gaps, respectively) and a set of AOT fields that differed only in the size and location of artificially created gaps. The Cumulative Semivariogram (CSV) was found to be sensitive to the spatial distribution of gap areas and, thus, useful for assessing the sensitivity of the fused data to spatial gaps.

Leptoukh, Gregory↗

A sampling procedure to guide the collection of narrow-band, high-resolution spatially and spectrally representative reflectance data

A multistage sampling procedure using image processing, geographical information systems, and analytical photogrammetry is presented which can be used to guide the collection of representative, high-resolution spectra and discrete reflectance targets for future satellite sensors. The procedure is general and can be adapted to characterize areas as small as minor watersheds and as large as multistate regions. Beginning with a user-determined study area, successive reductions in size and spectral variation are performed using image analysis techniques on data from the Multispectral Scanner, orbital and simulated Thematic Mapper, low altitude photography synchronized with the simulator, and associated digital data. An integrated image-based geographical information system supports processing requirements.

Brand, R. R.↗

Report of the x ray and gamma ray sensors panel

Overall five major areas of technology are recommended for development in order to meet the science requirements of the Astrotech 21 mission set. These are: detectors for high resolution gamma ray spectroscopy, cryogenic detectors for improved x ray spectral and spatial resolution, advanced x ray charge coupled devices (CCDs) for higher energy resolution and larger format, extension to higher energies, liquid and solid position sensitive detectors for improving stopping power in the energy range 5 to 500 keV and 0.2 to 2 MeV. Development plans designed to achieve the desired capabilities on the time scales required by the technology freeze dates have been recommended in each of these areas.

Szymkowiak, Andrew↗

Joint Characterization of Vegetation by Satellite Observations from Visible to Microwave Wavelengths - A Sensitivity Analysis

This study presents an evaluation and comparison of visible, near-infrared, passive, and active microwave observations for vegetation characterization on a global basis for a year, with spatial resolution compatible with climatological studies. Visible and near-infrared observations along with the Normalized Difference Vegetation Index come from the Advanced Very High Resolution Radiometer. An atlas of monthly mean microwave land surface emissivities from 19 to 85 GHz has been calculated from the Special Sensor Microwave/Imager for a year, suppressing the atmospheric problems encountered with the use of simple channel combinations. The active microwave measurements are provided by the ERS-1 scatterometer at 5.25 GHz. The capacity to discriminate between vegetation types and to detect the vegetation phenology is assessed in the context of a vegetation classification obtained from in situ observations. A clustering technique derived from the Kohonen topological maps is used to merge the three data sets and interpret their relative variations. NDVI varies with vegetation density but is not very sensitive in semiarid environments and in forested areas. Spurious seasonal cycles and large spatial variability in several areas suggest that atmospheric contamination and/or solar zenith angle drift still affect the NDVI.

NORMALIZED DIFFERENCE VEGETATIVE INDEX↗

Two 28-nm front-end ASICs for ultra-fine spatial resolution and precision timing to be 3D integrated with 12 LGADs

The 3DIntSenS Collaboration—a joint effort between SLAC, Fermilab, and LLNL—is developing enabling technologies for next-generation radiation imaging detectors that combine ultra-fine spatial resolution (about 10 µm) with precision timing (<20 ps), while maintaining low power <1 W/cm2 and high data throughput. The approach leverages 3D integration between advanced CMOS readout ASICs and finely pixelated LGAD sensors to achieve the performance and scalability required for large-area, high-rate applications. High-granularity, precision-timing detectors are essential for scientific advances in HEP, NP, BES, and FES, but widespread adoption is limited by the cost and complexity of 3D integration. To close this gap, the collaboration is developing LGAD sensors compatible with 12-inch commercial CMOS processes, enabling cost-effective integration with high-performance ASICs under development. We present two 28 nm CMOS ASIC prototypes, including a low-jitter front end, and in-pixel TDC demonstrating sub-10 ps timing resolution. These advances represent a critical step toward scalable, high-resolution radiation imaging systems for future scientific instrumentation.

England, Troy [Fermilab] (ORCID:0000000154405255)↗

Two 28-nm front-end ASICs for ultra-fine spatial resolution and precision timing to be 3D integrated with 12 LGADs

The 3DIntSenS Collaboration—a joint effort between SLAC, Fermilab, and LLNL—is developing enabling technologies for next-generation radiation imaging detectors that combine ultra-fine spatial resolution (about 10 µm) with precision timing (<20 ps), while maintaining low power <1 W/cm2 and high data throughput. The approach leverages 3D integration between advanced CMOS readout ASICs and finely pixelated LGAD sensors to achieve the performance and scalability required for large-area, high-rate applications. High-granularity, precision-timing detectors are essential for scientific advances in HEP, NP, BES, and FES, but widespread adoption is limited by the cost and complexity of 3D integration. To close this gap, the collaboration is developing LGAD sensors compatible with 12-inch commercial CMOS processes, enabling cost-effective integration with high-performance ASICs under development. We present two 28 nm CMOS ASIC prototypes, including a low-jitter front end, and in-pixel TDC demonstrating sub-10 ps timing resolution. These advances represent a critical step toward scalable, high-resolution radiation imaging systems for future scientific instrumentation.

England, Troy [Fermilab] (ORCID:0000000154405255)↗

The factor of scale in remote sensing

A method that measures the spatial structure of images as a function of spatial resolution is presented for selecting the appropriate scale for remote sensing. Graphs are obtained by imaging the scene at fine resolution and then collapsing the image to successively coarser resolutions while calculating the local variance. For the spatial resolution of SPOT and TM imagery, local image variance is relatively high for forested and urban/suburban environments, indicating that information-extraction techniques using texture, context, and mixture modeling are appropriate for these sensor systems. For agricultural environments where local variance is low, more traditional classifiers are appropriate.

Woodcock, Curtis E.↗

A snow wetness retrieval algorithm for SAR

The objectives of this study are: (1) to evaluate the backscattering signals response to snow wetness; and (2) to develop an algorithm for snow wetness measurement using C-band polarimetric synthetic aperture radar (SAR). In hydrological investigations, modeling and forecasting of snowmelt runoff requires information about snowpack properties and their spatial variability. In particular, timely measurement of snow parameters is needed for operational hydrology. The liquid water content of snowpack is one of the important parameters. Active microwave sensors are highly sensitive to liquid water in the snowpack because of the large dielectric contrast between ice and water in the microwave spectrum. They are not affected by weather and have a spatial resolution compatible with the topographic variation in alpine regions. However, a quantitative algorithm for retrieval snow wetness has not yet been developed.

Shi, Jian-Cheng↗

Piloted studies of Enhanced or Synthetic Vision display parameters

This paper summarizes the results of several studies conducted at Langley Research Center over the past few years. The purposes of these studies were to investigate parameters of pictorial displays and imaging sensors that affect pilot approach and landing performance. Pictorial displays have demonstrated exceptional tracking performance and improved the pilots' spatial awareness. Stereopsis cueing improved pilot flight performance and reduced pilot stress. Sensor image parameters such as increased field-of-view. faster image update rate, and aiding symbology improved flare initiation. Finer image resolution and magnification improved attitude control performance parameters.

Harris, Randall L., Sr.↗