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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.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

The X-ray Microcalorimeter Spectrometer (XMS): A Reference Cryogenic Instrument Design for Constellation-X

Constellation-X, a mission now belonging to the Beyond Einstein initiative, is being planned to inherit the x-ray sky from Chandra, XMM-Newton and Astro-E. The first two of four observatories in the constellation will be launched together in 2013 and followed a year later by the launch of the remaining two. The four will independently orbit the Sun-Earth Lagrange point L2. An instrument compliment resides in the Focal Plane Module (FPM) of each observatory 10 m from the Optics Module and consists of three Hard X-ray Telescope (HXT) detectors, a Reflection Grating Spectrometer (RGS) focal plane CCD camera and an X-ray Microcalorimeter Spectrometer (XMS). Instrument awards are scheduled for early 2006. The reference detector for XMS is a 32 x 32 array of microcalorimetric superconducting Transition Edge Sensors (TES). Each pixel casts a variable resistance in a SQUID based multiplexed readout circuit which is coupled to series SQUID arrays for amplification and finally read out by external electronics. A multi-stage continuous ADR will provide the stable 50 mK desired for the TES array and a stable 1 K for the series SQUID arrays while also lifting thermal parasitic and inefficiency loads to a 6 K cryocooler interface. The 6 K cryocooler is expected to emerge from the joint-project Advanced Cryocooler Technology Development Program (ACTDP) in which Constellation-X is an active participant. Project Pre-Formulation activities are marked by extensive technology development necessitating early, but realistic, thermal and cooling load requirements for ADR and ACTDP-cryocooler design points. Such requirements are driven by the encompassing XMS cryostat and ultimately by the thermal environment imposed by the FPM. It is further desired that the XMS instrument be able to operate on its side in the laboratory, with a warm vacuum shell, during an extensive calibration regime. It is that reference system design of the XMS instrument (microcalorimeter, ADR, cryocooler and cryostat) which is the subject of this paper.

Whitehouse, Paul L.↗
DOE OSTI2022

The Illumination of Thunderclouds by Lightning: 1. The Extent and Altitude of Optical Lightning Sources

Abstract Optical space‐based lightning sensors including NOAA's Geostationary Lightning Mapper (GLM) detect lightning though its transient illumination of the surrounding clouds. What space‐based optical lightning sensors measure is influenced by the physical attributes of the light source, the location of the source within the cloud scene, and the spatial variations in cloud composition. We focus on the lightning channels that serve as optical sources for GLM groups and flashes in this first part of our thundercloud illumination study. We match Lightning Mapping Array (LMA) sources with GLM groups and flashes during two thunderstorms to examine channel segments that are active during optical emission. We find that in each storm, the LMA sources matched with GLM groups are small (median: 3 km) compared to GLM pixels (nominal: 8 km), and preferentially come from high altitudes in the cloud (>8–10 km). The detection advantage for high‐altitude sources permits GLM to resolve faint optical pulses near the cloud top that might be missed from lower altitudes. However, the most energetic groups can be detected from all altitudes, and the largest groups largely originate at low altitudes. The relationship between group energy and illuminated area depends on flash development within the cloud medium, and flash development into different cloud regions can be identified by tracking GLM metrics of cloud illumination over time.

58 GEOSCIENCES↗
NASA NTRSDate not supplied

Examining Soil Freeze/Thaw Remote Sensing Using NASA’s SLAPex Freeze/Thaw Airborne Campaign

Around half the exposed land of the Northern Hemisphere experiences seasonal freezing and thawing. The changes to the soil thermal, hydraulic, and mechanical properties are large and these, in turn, exert significant controls on the water, energy, and carbon cycles of the affected regions. Wide-area freeze/thaw discrimination via microwave remote sensing is possible using both passive and active techniques. We explore freeze/thaw remote sensing using observations from NASA’s Scanning L-band Active Passive (SLAP) airborne sensor during the SLAPex Freeze/Thaw campaign near Winnipeg, Canada in November, 2015. SLAP is an airborne simulator of the Soil Moisture Active Passive (SMAP) satellite mission. The SLAPex Freeze/Thaw dataset is a unique dataset that allows comparison of airborne-derived freeze/thaw state (plus soil moisture for thawed areas) against in-situ ground truth, satellite-derived freeze/thaw from SMAP, as well as tower-based passive microwave freeze/thaw observations. The sensitivity of passive and active microwave sensing to different depths of freezing and different dielectric models (when soil moisture is retrieved) is examined, and the spatial scaling of heterogeneous frozen/thawed pixels is also explored. Implications for the accuracy of satellite-based freeze/thaw discrimination are discussed.

Edward Kim↗
DOE OSTI2024

Smart Pixels: In-pixel AI for on-sensor data filtering

We present a smart pixel prototype readout integrated circuit (ROIC) designed in CMOS 28 nm bulk process, with in-pixel implementation of an artificial intelligence (AI) / machine learning (ML) based data filtering algorithm designed as proof-of-principle for a Phase III upgrade at the Large Hadron Collider (LHC) pixel detector. The first version of the ROIC consists of two matrices of 256 smart pixels, each 25$\times$25 $\mu$m$^2$ in size. Each pixel consists of a charge-sensitive preamplifier with leakage current compensation and three auto-zero comparators for a 2-bit flash-type ADC. The frontend is capable of synchronously digitizing the sensor charge within 25 ns. Measurement results show an equivalent noise charge (ENC) of $\sim$30e$^-$ and a total dispersion of $\sim$100e$^-$ The second version of the ROIC uses a fully connected two-layer neural network (NN) to process information from a cluster of 256 pixels to determine if the pattern corresponds to highly desirable high-momentum particle tracks for selection and readout. The digital NN is embedded in-between analog signal processing regions of the 256 pixels without increasing the pixel size and is implemented as fully combinatorial digital logic to minimize power consumption and eliminate clock distribution, and is active only in the presence of an input signal. The total power consumption of the neural network is $\sim$ 300 $\mu$W. The NN performs momentum classification based on the generated cluster patterns and even with a modest momentum threshold, it is capable of 54.4% - 75.4% total data rejection, opening the possibility of using the pixel information at 40MHz for the trigger. The total power consumption of analog and digital functions per pixel is $\sim$ 6 $\mu$W per pixel, which corresponds to $\sim$ 1 W/cm$^2$ staying within the experimental constraints.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2020

Evaluation of the MODIS Collection 6 Multilayer Cloud Detection Algorithm Through Comparisons with Cloudsat Cloud Profiling Radar and CALIPSO CALIOP Products

Since multilayer cloud scenes are common in the atmosphere and can be an important source of uncertainty in passive satellite sensor cloud retrievals, the MODIS MOD06 and MYD06 standard cloud optical property products include a multilayer cloud detection algorithm to assist with data quality assessment. This paper presents an evaluation of the Aqua MODIS MYD06 Collection 6 multilayer cloud detection algorithm through comparisons with active Cloud Profiling Radar (CPR) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) products that have the ability to provide cloud vertical distributions and directly classify multilayer cloud scenes and layer properties. To compare active sensor products with an imager such as MODIS, it is first necessary to define multilayer clouds in the context of their radiative impact on cloud retrievals. Three main parameters have thus been considered in this evaluation: (1) the maximum separation distance between two cloud layers, (2) the thermodynamic phase of those layers and (3) the upper-layer cloud optical thickness. The impact of including the Pavolonis–Heidinger multilayer cloud detection algorithm, introduced in Collection 6, to assist with multilayer cloud detection has also been assessed. For the year 2008, the MYD06 C6 multilayer cloud detection algorithm identifies roughly 20% of all cloudy pixels as multilayer (decreasing to about 13% if the Pavolonis–Heidinger algorithm output is not used). Evaluation against the merged CPR and CALIOP2B-CLDCLASS-lidar product shows that the MODIS multilayer detection results are quite sensitive to how multilayer clouds are defined in the radar and lidar product and that the algorithm performs better when the optical thickness of the upper cloud layer is greater than about 1.2 with a minimum layer separation distance of 1 km. Finally, we find that filtering the MYD06 cloud optical properties retrievals using the multilayer cloud flag improves aggregated statistics, particularly for ice cloud effective radius.

MODIS↗
DOE OSTI2024

Smart Pixels: In-pixel AI for on-sensor data filtering

We present a smart pixel prototype readout integrated circuit (ROIC) designed in CMOS 28 nm bulk process, with in-pixel implementation of an artificial intelligence (AI) / machine learning (ML) based data filtering algorithm designed as proof-of-principle for a Phase III upgrade at the Large Hadron Collider (LHC) pixel detector. The first version of the ROIC consists of two matrices of 256 smart pixels, each 25$\times$25 µm\textsuperscript{2} in size. Each pixel consists of a charge-sensitive preamplifier with leakage current compensation and three auto-zero comparators for a 2-bit flash-type ADC. The frontend is capable of synchronously digitizing the sensor charge within 25 ns. Measurement results show an equivalent noise charge (ENC) of $\sim$30e\textsuperscript{-} and a total dispersion of $\sim$100e\textsuperscript{-} The second version of the ROIC uses a fully connected two-layer neural network (NN) to process information from a cluster of 256 pixels to determine if the pattern corresponds to highly desirable high-momentum particle tracks for selection and readout. The digital NN is embedded in-between analog signal processing regions of the 256 pixels without increasing the pixel size and is implemented as fully combinatorial digital logic to minimize power consumption and eliminate clock distribution, and is active only in the presence of an input signal. The total power consumption of the neural network is $\sim$ 300 $\mu$W. The NN performs momentum classification based on the generated cluster patterns and even with a modest momentum threshold, it is capable of 54.4\% – 75.4\% total data rejection, opening the possibility of using the pixel information at 40MHz for the trigger. The total power consumption of analog and digital functions per pixel is $\sim$ 6 $\mu$W per pixel, which corresponds to $\sim$ 1 W/cm\textsuperscript{2} staying within the experimental constraints.

Parpillon, Benjamin↗
DOE OSTI2022

A laser powder bed fusion system for operando synchrotron x-ray imaging and correlative diagnostic experiments at the Stanford Synchrotron Radiation Lightsource

Laser powder bed fusion (LPBF) is a highly dynamic multi-physics process used for the additive manufacturing (AM) of metal components. Improving process understanding and validating predictive computational models require high-fidelity diagnostics capable of capturing data in challenging environments. Synchrotron x-ray techniques play a vital role in the validation process as they are the only in situ diagnostic capable of imaging sub-surface melt pool dynamics and microstructure evolution during LPBF-AM. In this article, a laboratory scale system designed to mimic LPBF process conditions while operating at a synchrotron facility is described. The system is implemented with process accurate atmospheric conditions, including an air knife for active vapor plume removal. Significantly, the chamber also incorporates a diagnostic sensor suite that monitors emitted optical, acoustic, and electronic signals during laser processing with coincident x-ray imaging. The addition of the sensor suite enables validation of these industrially compatible single point sensors by detecting pore formation and spatter events and directly correlating the events with changes in the detected signal. Experiments in the Ti–6Al–4V alloy performed at the Stanford Synchrotron Radiation Lightsource using the system are detailed with sufficient sampling rates to probe melt pool dynamics. X-ray imaging captures melt pool dynamics at frame rates of 20 kHz with a 2 µm pixel resolution, and the coincident diagnostic sensor data are recorded at 470 kHz. Furthermore, this work shows that the current system enables the in situ detection of defects during the LPBF process and permits direct correlation of diagnostic signatures at the exact time of defect formation.

36 MATERIALS SCIENCE↗
NASA NTRS2010

Australian Soil Moisture Field Experiments in Support of Soil Moisture Satellite Observations

Large-scale field campaigns provide the critical fink between our understanding retrieval algorithms developed at the point scale, and algorithms suitable for satellite applications at vastly larger pixel scales. Retrievals of land parameters must deal with the substantial sub-pixel heterogeneity that is present in most regions. This is particularly the case for soil moisture remote sensing, because of the long microwave wavelengths (L-band) that are optimal. Yet, airborne L-band imagers have generally been large, heavy, and required heavy-lift aircraft resources that are expensive and difficult to schedule. Indeed, US soil moisture campaigns, have been constrained by these factors, and European campaigns have used non-imagers due to instrument and aircraft size constraints. Despite these factors, these campaigns established that large-scale soil moisture remote sensing was possible, laying the groundwork for satellite missions. Starting in 2005, a series of airborne field campaigns have been conducted in Australia: to improve our understanding of soil moisture remote sensing at large scales over heterogeneous areas. These field data have been used to test and refine retrieval algorithms for soil moisture satellite missions, and most recently with the launch of the European Space Agency's Soil Moisture Ocean Salinity (SMOS) mission, to provide validation measurements over a multi-pixel area. The campaigns to date have included a preparatory campaign in 2005, two National Airborne Field Experiments (NAFE), (2005 and 2006), two campaigns to the Simpson Desert (2008 and 2009), and one Australian Airborne Cal/val Experiment for SMOS (AACES), just concluded in the austral spring of 2010. The primary airborne sensor for each campaign has been the Polarimetric L-band Microwave Radiometer (PLMR), a 6-beam pushbroom imager that is small enough to be compatible with light aircraft, greatly facilitating the execution of the series of campaigns, and a key to their success. An L-band imaging radar is being added to the complement to provide simultaneous active-passive L-band observations, for algorithm development activities in support of NASA's upcoming Soil Moisture Active Passive (.S"M) mission. This paper will describe the campaigns, their objectives, their datasets, and some of the unique advantages of working with small/light sensors and aircraft. We will also review the main scientific findings, including improvements to the SMOS retrieval algorithm enabled by NAFE observations and the evaluation of the Simpson Desert as a calibration target for L-band satellite missions. Plans for upcoming campaigns will also be discussed.

Kim, Edward↗
DOE OSTI2023

First results from a multiplexed and massive instrument with sub-electron noise Skipper-CCDs

Here, we present a new instrument composed of a large number of sub-electron noise Skipper-CCDs operated with a two stage analog multiplexed readout scheme suitable for scaling to thousands of channels. New, thick, 1.35 Mpix sensors, from a new foundry, are glued into a Multi-Chip Module (MCM) printed circuit board on a ceramic substrate which has 16 sensors each. The instrument, that can hold up-to 16 MCMs, a total of 256 Skipper-CCD sensors (called a Super-Module with ≈ 130 grams of active mass and 346 Mpix), is part of the R&D effort of the OSCURA experiment which will have ≈ 94 super-modules. Experimental results with 10 MCMs and 160 Skipper-CCDs sensors are presented in this paper. This is already the largest ever built instrument with single electron sensitivity CCDs using nondestructive readout, both, in terms of active mass and number of channels.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2003

Beyond Solar-B: MTRAP, the Magnetic Transition Region Probe

The next generation of solar missions will reveal and measure fine-scale solar magnetic fields and their effects in the solar atmosphere at heights, small scales, sensitivities, and fields of view well beyond the reach of Solar-B. The necessity for, and potential of, such observations for understanding solar magnetic fields, their generation in and below the photosphere, and their control of the solar atmosphere and heliosphere, were the focus of a science definition workshop, 'High-Resolution Solar Magnetography from Space: Beyond Solar-B,' held in Huntsville Alabama in April 2001. Forty internationally prominent scientists active in solar research involving fine-scale solar magnetism participated in this Workshop and reached consensus that the key science objective to be pursued beyond Solar-B is a physical understanding of the fine-scale magnetic structure and activity in the magnetic transition region, defined as the region between the photosphere and corona where neither the plasma nor the magnetic field strongly dominates the other. The observational objective requires high cadence (less than 10s) vector magnetic field maps, and spatially resolved spectra from the IR, visible, vacuum UV, to the EUV at high resolution (less than 50km) over a large FOV (approximately 140,000 km). A polarimetric resolution of one part in ten thousand is required to measure transverse magnetic fields of less than 30G. The latest SEC Roadmap includes a mission identified as MTRAP to meet these requirements. Enabling technology development requirements include large, lightweight, reflecting optics, large format sensors (16K x 16K pixels) with high QE at 150 nm, and extendable spacecraft structures. The Science Organizing Committee of the Beyond Solar-B Workshop recommends that: (1) Science and Technology Definition Teams should be established in FY04 to finalize the science requirements and to define technology development efforts needed to ensure the practicality of MTRAP's observational goals; (2) The necessary technology development funding should be included in Code S budgets for FY06 and beyond to prepare MTRAP for a new start no later than the nominal end of the Solar-B mission, around 2010.

Davis, John M.↗
NASA NTRS2011

Dynamic Black-Level Correction and Artifact Flagging for Kepler Pixel Time Series

Methods applied to the calibration stage of Kepler pipeline data processing [1] (CAL) do not currently use all of the information available to identify and correct several instrument-induced artifacts. These include time-varying crosstalk from the fine guidance sensor (FGS) clock signals, and manifestations of drifting moire pattern as locally correlated nonstationary noise, and rolling bands in the images which find their way into the time series [2], [3]. As the Kepler Mission continues to improve the fidelity of its science data products, we are evaluating the benefits of adding pipeline steps to more completely model and dynamically correct the FGS crosstalk, then use the residuals from these model fits to detect and flag spatial regions and time intervals of strong time-varying black-level which may complicate later processing or lead to misinterpretation of instrument behavior as stellar activity.

Kolodziejczak, J. J.↗
NASA NTRS2005

Generic Sensor Modeling Using Pulse Method

Recent development of high spatial resolution satellites such as IKONOS, Quickbird and Orbview enable observation of the Earth's surface with sub-meter resolution. Compared to the 30 meter resolution of Landsat 5 TM, the amount of information in the output image was dramatically increased. In this era of high spatial resolution, the estimation of spatial quality of images is gaining attention. Historically, the Modulation Transfer Function (MTF) concept has been used to estimate an imaging system's spatial quality. Sometimes classified by target shapes, various methods were developed in laboratory environment utilizing sinusoidal inputs, periodic bar patterns and narrow slits. On-orbit sensor MTF estimation was performed on 30-meter GSD Landsat4 Thematic Mapper (TM) data from the bridge pulse target as a pulse input . Because of a high resolution sensor s small Ground Sampling Distance (GSD), reasonably sized man-made edge, pulse, and impulse targets can be deployed on a uniform grassy area with accurate control of ground targets using tarps and convex mirrors. All the previous work cited calculated MTF without testing the MTF estimator's performance. In previous report, a numerical generic sensor model had been developed to simulate and improve the performance of on-orbit MTF estimating techniques. Results from the previous sensor modeling report that have been incorporated into standard MTF estimation work include Fermi edge detection and the newly developed 4th order modified Savitzky-Golay (MSG) interpolation technique. Noise sensitivity had been studied by performing simulations on known noise sources and a sensor model. Extensive investigation was done to characterize multi-resolution ground noise. Finally, angle simulation was tested by using synthetic pulse targets with angles from 2 to 15 degrees, several brightness levels, and different noise levels from both ground targets and imaging system. As a continuing research activity using the developed sensor model, this report was dedicated to MTF estimation via pulse input method characterization using the Fermi edge detection and 4th order MSG interpolation method. The relationship between pulse width and MTF value at Nyquist was studied including error detection and correction schemes. Pulse target angle sensitivity was studied by using synthetic targets angled from 2 to 12 degrees. In this report, from the ground and system noise simulation, a minimum SNR value was suggested for a stable MTF value at Nyquist for the pulse method. Target width error detection and adjustment technique based on a smooth transition of MTF profile is presented, which is specifically applicable only to the pulse method with 3 pixel wide targets.

Helder, Dennis L.↗
NASA NTRS2012

Variable Sampling Mapping

The performance of an optical system (for example, a telescope) is limited by the misalignments and manufacturing imperfections of the optical elements in the system. The impact of these misalignments and imperfections can be quantified by the phase variations imparted on light traveling through the system. Phase retrieval is a methodology for determining these variations. Phase retrieval uses images taken with the optical system and using a light source of known shape and characteristics. Unlike interferometric methods, which require an optical reference for comparison, and unlike Shack-Hartmann wavefront sensors that require special optical hardware at the optical system's exit pupil, phase retrieval is an in situ, image-based method for determining the phase variations of light at the system s exit pupil. Phase retrieval can be used both as an optical metrology tool (during fabrication of optical surfaces and assembly of optical systems) and as a sensor used in active, closed-loop control of an optical system, to optimize performance. One class of phase-retrieval algorithms is the iterative transform algorithm (ITA). ITAs estimate the phase variations by iteratively enforcing known constraints in the exit pupil and at the detector, determined from modeled or measured data. The Variable Sampling Mapping (VSM) technique is a new method for enforcing these constraints in ITAs. VSM is an open framework for addressing a wide range of issues that have previously been considered detrimental to high-accuracy phase retrieval, including undersampled images, broadband illumination, images taken at or near best focus, chromatic aberrations, jitter or vibration of the optical system or detector, and dead or noisy detector pixels. The VSM is a model-to-data mapping procedure. In VSM, fully sampled electric fields at multiple wavelengths are modeled inside the phase-retrieval algorithm, and then these fields are mapped to intensities on the light detector, using the properties of the detector and optical system, for comparison with measured data. Ultimately, this model-to-data mapping procedure enables a more robust and accurate way of incorporating the exit-pupil and image detector constraints, which are fundamental to the general class of ITA phase retrieval algorithms.

Smith, Jeffrey, S.↗
DOE OSTI2024

Single-photon detection using large-scale high-temperature MgB2 sensors at 20 K

Abstract Ultra-fast single-photon detectors with high current density and operating temperature can benefit space and ground applications, including quantum optical communication systems, lightweight cryogenics for space crafts, and medical use. Here we demonstrate magnesium diboride (MgB 2 ) thin-film superconducting microwires capable of single-photon detection at 1.55 μ m optical wavelength. We used helium ions to alter the properties of MgB 2 , resulting in microwire-based detectors exhibiting single-photon sensitivity across a broad temperature range of up to 20 K, and detection efficiency saturation for 1 μ m wide microwires at 3.7 K. Linearity of detection rate vs incident power was preserved up to at least 100 Mcps. Despite the large active area of up to 400 × 400 μ m 2 , the reset time was found to be as low as ~ 1 ns. Our research provides possibilities for breaking the operating temperature limit and maximum single-pixel count rate, expanding the detector area, and raises inquiries about the fundamental mechanisms of single-photon detection in high-critical-temperature superconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2006

Analysis of Leaf Area Index and Fraction of PAR Absorbed by Vegetation Products from the Terra MODIS Sensor: 2000-2005

The analysis of two years of Collection 3 and five years of Collection 4 Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (FPAR) data sets is presented in this article with the goal of understanding product quality with respect to version (Collection 3 versus 4), algorithm (main versus backup), snow (snow-free versus snow on the ground), and cloud (cloud-free versus cloudy) conditions. Retrievals from the main radiative transfer algorithm increased from 55% in Collection 3 to 67% in Collection 4 due to algorithm refinements and improved inputs. Anomalously high LAI/FPAR values observed in Collection 3 product in some vegetation types were corrected in Collection 4. The problem of reflectance saturation and too few main algorithm retrievals in broadleaf forests persisted in Collection 4. The spurious seasonality in needleleaf LAI/FPAR fields was traced to fewer reliable input data and retrievals during the boreal winter period. About 97% of the snow covered pixels were processed by the backup Normalized Difference Vegetation Index-based algorithm. Similarly, a majority of retrievals under cloudy conditions were obtained from the backup algorithm. For these reasons, the users are advised to consult the quality flags accompanying the LAI and FPAR product.

Yang, Wenze↗
NASA NTRS1995

Laser-Directed Ranging System Implementing Single Camera System for Telerobotics Applications

The invention relates generally to systems for determining the range of an object from a reference point and, in one embodiment, to laser-directed ranging systems useful in telerobotics applications. Digital processing techniques are employed which minimize the complexity and cost of the hardware and software for processing range calculations, thereby enhancing the commercial attractiveness of the system for use in relatively low-cost robotic systems. The system includes a video camera for generating images of the target, image digitizing circuitry, and an associated frame grabber circuit. The circuit first captures one of the pairs of stereo video images of the target, and then captures a second video image of the target as it is partly illuminated by the light beam, suitably generated by a laser. The two video images, taken sufficiently close together in time to minimize camera and scene motion, are converted to digital images and then compared. Common pixels are eliminated, leaving only a digital image of the laser-illuminated spot on the target. Mw centroid of the laser illuminated spot is dm obtained and compared with a predetermined reference point, predetermined by design or calibration, which represents the coordinate at the focal plane of the laser illumination at infinite range. Preferably, the laser and camera are mounted on a servo-driven platform which can be oriented to direct the camera and the laser toward the target. In one embodiment the platform is positioned in response to movement of the operator's head. Position and orientation sensors are used to monitor head movement. The disparity between the digital image of the laser spot and the reference point is calculated for determining range to the target. Commercial applications for the system relate to active range-determination systems, such as those used with robotic systems in which it is necessary to determine the, range to a workpiece or object to be grasped or acted upon by a robot arm end-effector in response to commands generated by an operator. In one embodiment, the system provides a real-time image of the target for the operator as the robot approaches the object. The system is also adapted for use in virtual reality systems in which a remote object or workpiece is to be acted upon by a remote robot arm or other mechanism controlled by an operator.

Wells, Dennis L.↗
NASA NTRS2003

Use of MODIS-Derived Fire Radiative Energy to Estimate Smoke Aerosol Emissions over Different Ecosystems

Biomass burning is the main source of smoke aerosols and certain trace gases in the atmosphere. However, estimates of the rates of biomass consumption and emission of aerosols and trace gases from fires have not attained adequate reliability thus far. Traditional methods for deriving emission rates employ the use of emission factors e(sub x), (in g of species x per kg of biomass burned), which are difficult to measure from satellites. In this era of environmental monitoring from space, fire characterization was not a major consideration in the design of the early satellite-borne remote sensing instruments, such as AVHRR. Therefore, although they are able to provide fire location information, they were not adequately sensitive to variations in fire strength or size, because their thermal bands used for fire detection saturated at the lower end of fire radiative temperature range. As such, hitherto, satellite-based emission estimates employ proxy techniques using satellite derived fire pixel counts (which do not express the fire strength or rate of biomass consumption) or burned areas (which can only be obtained after the fire is over). The MODIS sensor, recently launched into orbit aboard EOS Terra (1999) and Aqua (2002) satellites, have a much higher saturation level and can, not only detect the fire locations 4 times daily, but also measures the at-satellite fire radiative energy (which is a measure of the fire strength) based on its 4 micron channel temperature. Also, MODIS measures the optical thickness of smoke and other aerosols. Preliminary analysis shows appreciable correlation between the MODIS-derived rates of emission of fire radiative energy and smoke over different regions across the globe. These relationships hold great promise for deriving emission coefficients, which can be used for estimating smoke aerosol emissions from MODIS active fire products. This procedure has the potential to provide more accurate emission estimates in near real-time, providing opportunities for various disaster management applications such as alerts, evacuation and, smoke dispersion forecasting.

Ichoku, Charles↗
NASA NTRS1992

EOS workstation

This final report summarizes the work done from mid-1989 until January 1992 to develop a prototype set of tools for the analysis of EOS-type images. Such images are characterized by great multiplicity and quantity. A single 'snapshot' of EOS-type imagery may contain several hundred component images so that on a particular pixel, one finds multiple gray values. A prototype EOS-sensor, AVIRIS, has 224 gray values at each pixel. The work focused on the ability to utilize very large images and continuously roam through those images, zoom and be able to hold more than one black and white or color image, for example for stereo viewing or for image comparisons. A second focus was the utilization of so-called 'image cubes', where multiple images need to be co-registered and then jointly analyzed, viewed, and manipulated. The target computer platform that was selected was a high-performance graphics superworkstation, Stardent 3000. This particular platform offered many particular graphics tools such as the Application Visualization System (AVS) or Dore, but it missed availability of commercial third-party software for relational data bases, image processing, etc. The project was able to cope with these limitations and a phase-3 activity is currently being negotiated to port the software and enhance it for use with a novel graphics superworkstation to be introduced into the market in the Spring of 1993.

Leberl, Franz↗