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At least 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Recent Enhancements of the Phased Array Mirror Extendible Large Aperture (PAMELA) Telescope Testbed at MSFC

Recent incremental upgrades to the Phased Array Mirror Extendible Large Aperture (PAMELA) telescope testbed have enabled the demonstration of phasing (with a monochromatic source) of clusters of primary mirror segments down to the diffraction limit. PAMELA upgrades include an improved Shack-Hartmann wavefront sensor, passive viscoelastic damping treatments for the voice-coil actuators, mechanical improvement of mirror surface figures, and optical bench baffling. This report summarizes the recent PAMELA upgrades, discusses the lessons learned, and presents a status of this unique testbed for wavefront sensing and control. The Marshall Space Flight Center acquired the Phased Array Mirror Extendible Large Aperture (PAMELA) telescope in 1993 after Kaman Aerospace was unable to complete integration and testing under the limited SDIO and DARPA funding. The PAMELA is a 36-segment, half-meter aperture, adaptive telescope which utilizes a Shack-Hartmann wavefront sensor, inductive coil edge sensors, voice coil actuators, imaging CCD cameras and interferometry for figure alignment, wavefront sensing and control. MSFC originally obtained the PAMELA to supplement its research in the interactions of control systems with flexible structures. In August 1994, complete tip, tilt and piston control was successfully demonstrated using the Shack-Hartmann wavefront sensor and the inductive edge sensors.

Rakoczy, John↗
NASA NTRS2001

Recent Enhancements of the Phased Array Mirror Extendible Large Aperture (PAMELA) Telescope Testbed at MSFC

Recent incremental upgrades to the Phased Array Mirror Extendible Large Aperture (PAMELA) telescope testbed have enabled the demonstration of phasing (with a monochromatic source) of clusters of primary mirror segments down to the diffraction limit. PAMELA upgrades include in improved Shack-Hartmann wavefront sensor, passive viscoelastic damping treatments for the voice-coil actuators, mechanical improvement of mirror surface figures, and optical bench baffling. This report summarizes the recent PAMELA upgrades, discusses the lessons learned, and presents a status of this unique testbed for wavefront sensing and control. The Marshall Space Flight Center acquired the Phased Array Mirror Extendible Large Aperture (PAMELA) telescope in 1993 after Kaman Aerospace was unable to complete integration and testing under the limited SDIO and DARPA funding. The PAMELA is a 36-segment, half-meter aperture, adaptive telescope which utilizes a Shack-Hartmann wavefront sensor, inductive coil edge sensors, voice coil actuators, imaging CCD cameras and interferometry for figure alignment, wavefront sensing and control. MSFC originally obtained the PAMELA to supplement its research in the interactions of control systems with flexible structures. In August 1994, complete tip, tilt and piston control was successfully demonstrated using the Shack-Hartmann wavefront sensor and the inductive edge sensors.

Rakoczy, John↗
NASA NTRS1973

Image processing techniques and applications to the Earth Resources Technology Satellite program

The Earth Resources Technology Satellite system is studied, with emphasis on sensors, data processing requirements, and image data compression using the Fast Fourier and Hadamard transforms. The ERTS-A system and the fundamentals of remote sensing are discussed. Three user applications (forestry, crops, and rangelands) are selected and their spectral signatures are described. It is shown that additional sensors are needed for rangeland management. An on-board information processing system is recommended to reduce the amount of data transmitted.

Polge, R. J.↗
NASA NTRS1975

Spline function approximation techniques for image geometric distortion representation

Least squares approximation techniques were developed for use in computer aided correction of spatial image distortions for registration of multitemporal remote sensor imagery. Polynomials were first used to define image distortion over the entire two dimensional image space. Spline functions were then investigated to determine if the combination of lower order polynomials could approximate a higher order distortion with less computational difficulty. Algorithms for generating approximating functions were developed and applied to the description of image distortion in aircraft multispectral scanner imagery. Other applications of the techniques were suggested for earth resources data processing areas other than geometric distortion representation.

Anuta, P. E.↗
NASA NTRS1966

New television camera eliminates vidicon tube

Small, lightweight camera systems use solid state imaging devices in the form of phototransistor mosaic sensors instead of vidicon tubes for light sensing and image conversion. The digital logic circuits scan the sensor mosaic at 60 frames per second to produce pictures composed of a series of dots rather than lines.

Source record↗
NASA NTRS1978

Theory on data processing and instrumentation

A selection of NASA Earth observations programs are reviewed, emphasizing hardware capabilities. Sampling theory, noise and detection considerations, and image evaluation are discussed for remote sensor imagery. Vision and perception are considered, leading to numerical image processing. The use of multispectral scanners and of multispectral data processing systems, including digital image processing, is depicted. Multispectral sensing and analysis in application with land use and geographical data systems are also covered.

Billingsley, F. C.↗
NASA NTRS1983

Radar image registration and rectification

Two techniques for radar image registration and rectification are presented. In the registration method, a general 2-D polynomial transform is defined to accomplish the geometric mapping from one image into the other. The degree and coefficients of the polynomial are obtained using an a priori found tiepoint data set. In the second part of the paper, a rectification procedure is developed that models the distortion present in the radar image in terms of the radar sensor's platform parameters and the topographic variations of the imaged scene. This model, the ephemeris data and the digital topographic data are then used in rectifying the radar image. The two techniques are then used in registering and rectifying two examples of radar imagery. Each method is discussed as to its benefits, shortcomings and registration accuracy.

Naraghi, M.↗
NASA NTRS1991

Image based tracking approaches to AR/C at the Johnson Space Center

Automated Rendezvous and Capture (AR&C) requires the determination of the six degrees of freedom relating two free bodies. Sensor systems that can provide such information have varying sizes, weights, power requirements, complexities and accuracies. One type of sensor system which can provide several key advantages is an image based tracking system, or better known as a machine vision system. By image based tracking we mean that the sensor is some imaging device such as one or more video cameras, from which the tracking parameters necessary to support the rendezvous and capture operations (range, attitude, etc.) can be derived. Image based tracking offers many advantages such as relative hardware simplicity and reprogrammability. These advantages must be weighed against the disadvantages of these systems, such as limited operational range, poorer accuracy at greater distances and sensitivity to lighting conditions. However, with properly designed algorithms and targets these disadvantages can be minimized for many important applications. Rigorous testing in realistic environments can further increase the robustness and reliability of these systems. This presentation describes the facilities used at JSC to support AR&C image based tracking development and the details of our binocular stereo approach to image based tracking.

Fisher, Timothy E.↗
NASA NTRS1991

A light intensity function suitable for multimode fiber-optic sensors

Intensity distribution functions on the image plane are derived under the assumption that a multimode optic fiber is illuminated by a light source which can be approximated by infinite uniangular beams carrying equal power. The application of the theory to a Lambertian source is discussed. Experimental results, based on the observation of the light intensity distribution imaged on an opaque screen and collected by a digital camera, are presented. The theoretical and experimental data are compared to verify that the intensity function is an accurate model for describing the realistic approach to sensor design. The limitations of the uniangular and uniform intensity distribution models are discussed on the basis of theoretical and experimental results.

He, Gang↗
NASA NTRS1991

Collision avoidance sensor skin

The objective was to totally eliminate the possibility of a robot (or any mechanism for that matter) inducing a collision in space operations. We were particularly concerned that human beings were safe under all circumstances. This was apparently accomplished, and it is shown that GSFC has a system that is ready for space qualification and flight. However, it soon became apparent that much more could be accomplished with this technology. Payloads could be made invulnerable to collision avoidance and the blind spots behind them eliminated. This could be accomplished by a simple, non-imaging set of 'Capaciflector' sensors on each payload. It also is evident that this system could be used to align and dock the system with a wide margin of safety. Throughout, lighting problems could be ignored, and unexpected events and modeling errors taken in stride. At the same time, computational requirements would be reduced. This can be done in a simple, rugged, reliable manner that will not disturb the form factor of space systems. It will be practical for space applications. The lab experiments indicate we are well on the way to accomplishing this. Still, the research trail goes deeper. It now appears that the sensors can be extended to end effectors to provide precontact information and make robot docking (or any docking connection) very smooth, with minimal loads impacted back into the mating structures. This type of ability would be a major step forward in basic control techniques in space. There are, however, baseline and restructuring issues to be tackled. The payloads must get power and signals to them from the robot or from the astronaut servicing tool. This requires a standard electromechanical interface. Any of several could be used. The GSFC prototype shown in this presentation is a good one. Sensors with their attendant electronics must be added to the payloads, end effectors, and robot arms and integrated into the system.

Source record↗
NASA NTRS2009

Assessment of the Short-Term Radiometric Stability between Terra MODIS and Landsat 7 ETM+ Sensors

The Landsat 7 (L7) Enhanced Thematic Mapper (ETM+) sensor was launched on April 15th, 1999 and has been in operation for over nine years. It has six reflective solar spectral bands located in the visible and shortwave infrared part of the electromagnetic spectrum (0.5 - 2.5 micron) at a spatial resolution of 30 m. The on-board calibrators are used to monitor the on-orbit sensor system changes. The ETM+ performs solar calibrations using on-board Full Aperture Solar Calibrator (FASC) and the Partial Aperture Solar Calibrator (PASC). The Internal Calibrator Lamp (IC) lamps, a blackbody and shutter optics constitute the on-orbit calibration mechanism for ETM+. On 31 May 2003, a malfunction of the scan-line corrector (SLC) mirror assembly resulted in the loss of approximately 22% of the normal scene area. The missing data affects most of the image with scan gaps varying in width from one pixel or less near the centre of the image to 14 pixels along the east and west edges of the image, creating a wedge-shaped pattern. However, the SLC failure has no impacts on the radiometric performance of the valid pixels. On December 18, 1999, the Moderate Resolution Imaging Spectroradiometer (MODIS) Proto-Flight Model (PFM) was launched on-board the NASA's EOS Terra spacecraft. Terra MODIS has 36 spectral bands with wavelengths ranging from 0.41 to 14.5 micron and collects data over a wide field of view angle (+/-55 deg) at three nadir spatial resolutions of 250 m, 500 in 1 km for bands 1 to 2, 3 to 7, and 8 to 36, respectively. It has 20 reflective solar bands (RSB) with spectral wavelengths from 0.41 to 2.1 micron. The RSB radiometric calibration is performed by using on-board solar diffuser (SD), solar diffuser stability monitor (SDSM), space-view (SV), and spectro-radiometric calibration assembly (SRCA). Through the SV port, periodic lunar observations are used to track radiometric response changes at different angles of incidence (AOI) of the scan mirror. As a part of the AM Constellation satellites, Terra MODIS flies approximately 30 minutes behind L7 ETM+ in the same orbit. The orbit of L7 is repetitive, circular, sunsynchronous, and near polar at a nominal altitude of 705 km (438 miles) at the Equator. The spacecraft crosses the Equator from north to south on a descending node between 10:00 AM and 10:15 AM. Circling the Earth at 7.5 km/sec, each orbit takes nearly 99 minutes. The spacecraft completes just over 14 orbits per day, covering the entire Earth between 81 degrees north and south latitude every 16 days. The longest continuous imaging swath that L7 sensor can collect is for a 14-minute subinterval contact period which is equivalent to 35 full WRS-2 scenes. On the other hand, Terra can provide the entire corresponding orbit with wider swath at any given ETM+ collection without contact time limitation. There are six spectral matching band pairs between MODIS (bands 3, 4, 1, 2, 6, 7) and ETM+ (bands 1, 2, 3, 4, 5, 7) sensor. MODIS has narrower spectral responses than ETM+ in all the bands. A short-term radiometric stability was evaluated using continuous ETM+ scenes within the contact period and the corresponding half orbit MODIS scenes. The near simultaneous earth observations (SNO) were limited by the smaller swath size of ETM+ (187 km) as compared to MODIS (2330 km). Two sets of continuous granules for MODIS and ETM+ were selected and mosaiced based on pixel geolocation information for non cloudy pixels over the North American continent. The Top-of- Atmosphere (TOA) reflectances were computed for the spectrally matching bands between ETM+ and MODIS over the regions of interest (ROI). The matching pixel pairs were aggregated from a finer to a coarser pixel resolution and the TOA reflectance values covering a wide dynamic range of the sensors were compared and analyzed. Considering the uncertainties of the absolute calibration of the both sensors, radiometric stability was verified for the band pairs. The Railroad Valley Playa, Nada (RVPN) was included in the path of this continuous orbit, which served as a verification point between the shortterm and the long-term trending results from previous studies. This work focuses on monitoring the short-term on-orbit stability of MODIS and the ETM+ RSB. It also provides an assessment of the absolute calibration differences between the two sensors over their wide dynamic ranges.

Choi, Taeyoung↗
NASA NTRS2018

Intercomparison of MODIS AQUA and VIIRS I-Band Fires and Emissions in an Agricultural Landscape - Implications for Air Pollution Research

Quantifying emissions from crop residue burning is crucial as it is a significant source of air pollution. In this study, we first compared the fire products from two different sensors, the Visible Infrared Imaging Radiometer Suite (VIIRS) 375 m active fire product (VNP14IMG) and Moderate Resolution Imaging Spectroradiometer (MODIS) 1 km fire product (MCD14ML) in an agricultural landscape, Punjab, India. We then performed an intercomparison of three different approaches for estimating total particulate matter (TPM) emissions which includes the fire radiative power (FRP) based approach using VIIRS and MODIS data, the Global Fire Emissions Database (GFED) burnt area emissions and a bottom-up emissions approach involving agricultural census data. Results revealed that VIIRS detected fires were higher by a factor of 4.8 compared to MODIS Aqua and Terra sensors. Further, VIIRS detected fires were higher by a factor of 6.5 than Aqua. The mean monthly MODIS Aqua FRP was found to be higher than the VIIRS FRP; however, the sum of FRP from VIIRS was higher than MODIS data due to the large number of fires detected by the VIIRS. Besides, the VIIRS sum of FRP was 2.5 times more than the MODIS sum of FRP. MODIS and VIIRS monthly FRP data were found to be strongly correlated (r2 = 0.98). The bottom-up approach suggested TPM emissions in the range of 88.19-91.19 Gg compared to 42.0-61.71 Gg, 42.59-58.75 Gg and 93.98-111.72 Gg using the GFED, MODIS FRP, and VIIRS FRP based approaches, respectively. Of the different approaches, VIIRS FRP TPM emissions were highest. Since VIIRS data are only available since 2012 compared to MODIS Aqua data which have been available since May 2002, a prediction model combining MODIS and VIIRS FRP was derived to obtain potential TPM emissions from 2003-2016. The results suggested a range of 2.56-63.66 (Gg) TPM emissions per month, with the highest crop residue emissions during November of each year. Our results on TPM emissions for seasonality matched the ground-based data from the literature. As a mitigation option, stringent policy measures are recommended to curtail agricultural residue burning in the study area.

Global Fire Emissions Database (GFED)↗
NASA NTRS2011

Automated Verification of Spatial Resolution in Remotely Sensed Imagery

Image spatial resolution characteristics can vary widely among sources. In the case of aerial-based imaging systems, the image spatial resolution characteristics can even vary between acquisitions. In these systems, aircraft altitude, speed, and sensor look angle all affect image spatial resolution. Image spatial resolution needs to be verified with estimators that include the ground sample distance (GSD), the modulation transfer function (MTF), and the relative edge response (RER), all of which are key components of image quality, along with signal-to-noise ratio (SNR) and dynamic range. Knowledge of spatial resolution parameters is important to determine if features of interest are distinguishable in imagery or associated products, and to develop image restoration algorithms. An automated Spatial Resolution Verification Tool (SRVT) was developed to rapidly determine the spatial resolution characteristics of remotely sensed aerial and satellite imagery. Most current methods for assessing spatial resolution characteristics of imagery rely on pre-deployed engineered targets and are performed only at selected times within preselected scenes. The SRVT addresses these insufficiencies by finding uniform, high-contrast edges from urban scenes and then using these edges to determine standard estimators of spatial resolution, such as the MTF and the RER. The SRVT was developed using the MATLAB programming language and environment. This automated software algorithm assesses every image in an acquired data set, using edges found within each image, and in many cases eliminating the need for dedicated edge targets. The SRVT automatically identifies high-contrast, uniform edges and calculates the MTF and RER of each image, and when possible, within sections of an image, so that the variation of spatial resolution characteristics across the image can be analyzed. The automated algorithm is capable of quickly verifying the spatial resolution quality of all images within a data set, enabling the appropriate use of those images in a number of applications.

Davis, Bruce↗
NASA NTRSDate not supplied

Determining True Sensor Spatial Resolution of Very High Resolution Optical Imagery

Some satellite data is delivered in images with gridded pixels. This gridded pixel size is often assumed to be the spatial resolution of the satellite sensor; however, this is not always the case. An image can be grided to any arbitrary pixel size, but the sensor resolution will remain constant. For example, an image with a pixel grid size much smaller than the sensor resolution will appear blurry along what should be sharp transitions. This discrepancy between an image’s pixel size and true sensor spatial resolution can be the source of much confusion and even misinformation among data users, which may lead them to waste time and resources on using images that do not suit their spatial resolution needs. This presentation will highlight our evaluation of the true spatial resolution of various government and commercial images in the pixel size range of 0.3 m to 60 m. Images evaluated include ESA’s Sentinel-2 (60 m, 20 m, 10 m pixels), USGS’s Landsat 8/9 (30 m & 15 m pixels), Planet’s SuperDoves (3 m pixels), BlackSky’s Globals (~1 m pixels), and the optical bands of Maxar’s WorldView-2 (2.4 m – 0.41 m pixels) and WorldView-3 (1.38 m – 0.31 m pixels). Our evaluation of true sensor spatial resolution, or ‘footprint size’ is based on the sensor’s line spread function (LSF). We calculate the width at half the height of the LSF to find the full width at half maximum (FWHM). The FWHM is how we report sensor spatial resolution. Different objects are examined for constructing the LSF depending on the sensor spatial resolution. Coarser resolution sensors in this evaluation such as Sentinel-2 and Landsat 8/9 are examined at bridges over a dark water background. The bright bridge acts as a line impulse, giving a sensor’s line spread function (LSF) in one direction. Additionally, we simulate the impacts of bridge width on the apparent LSF to obtain a true LSF without the effects of bridge width for these sensors. Finer resolution sensors will image the irregularities in bridges such as trusses, sidewalks, and in some cases painted lines, interfering with the LSF construction. Instead, these sensors are evaluated at large (60 m – 140 m) black and white checkerboards known as Cal/Val sites. At these locations, the image’s transition from black to white is extracted as an edge spread function (ESF). We calculate the derivative of this ESF to obtain the sensor’s LSF. From there, we find the FWHM as we do for the coarser resolution images. With the FWHM and pixel size, we determine how over- or under-sampled the images are. When the ratio of a sensor’s spatial resolution and the gridded image’s pixel size is less than 1, the image is considered under-sampled. In this case, each pixel’s information is unique but only a portion of that pixel’s ground area has been measured. On the other side, if the ratio is greater than 1, the image is considered over-sampled. That is, each pixel’s information is sourced from within the ground extent of the pixel and some extent outside additionally. We will show the true spatial resolution and the extent of over-/under-sampling in the imagery from ESA’s Sentinel-2 (60 m, 20 m, 10 m pixels), USGS’s Landsat 8/9 (30 m & 15 m pixels), Planet’s SuperDoves (3 m pixels), BlackSky’s Globals (~1 m pixels), and the optical bands of Maxar’s WorldView-2 (2.4 m – 0.41 m pixels) and WorldView-3 (1.38 m – 0.31 m pixels).

Alana Semple↗
NASA NTRS2004

Superconducting Digital Multiplexers for Sensor Arrays

Arrays of cryogenic microbolometers and other cryogenic detectors are being developed for infrared imaging. If the signal from each sensor is amplified, multiplexed, and digitized using superconducting electronics, then this data can be efficiently read out to ambient temperature with a minimum of noise and thermal load. HYPRES is developing an integrated system based on SQUID amplifiers, a high-resolution analog-to-digital converter (ADC) based on RSFQ (rapid single flux quantum) logic, and a clocked RSFQ multiplexer. The ADC and SQUIDs have already been demonstrated for other projects, so this paper will focus on new results of a digital multiplexer. Several test circuits have been fabricated using Nb Josephson technology and are about to be tested at T = 4.2 K, with a more complete prototype in preparation.

Kadin, Alan M.↗
NASA NTRS2007

SSC Geopositional Assessment of an AWiFS Image Orthorectified Product

The geopositional accuracy of an AWiFS (Advanced Wide Field Sensor) orthorectified product was evaluated. Specifically, the image products were acquired by the Indian Remote Sensing Resourcesat-1 satellite, then orthorectified by GeoEye . Analysis was performed using DOQs (digital orthophoto quadrangles) and other reference sources of similar accuracy. A total of six AWiFS images were characterized. These images were acquired over the continental United States from June through September 2005. The images were equally divided between the two AWiFS cameras. Forty to fifty check points were collected manually per scene and analyzed to determine overall circular error, estimates of horizontal bias, and other systematic errors.

Kenton, Ross↗
NASA NTRS2016

Imager-to-Radiometer In-flight Cross Calibration: RSP Radiometric Comparison with Airborne and Satellite Sensors

This work develops a method to compare the radiometric calibration between a radiometer and imagers hosted on aircraft and satellites. The radiometer is the airborne Research Scanning Polarimeter (RSP), which takes multi-angle, photo-polarimetric measurements in several spectral channels. The RSP measurements used in this work were coincident with measurements made by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), which was on the same aircraft. These airborne measurements were also coincident with an overpass of the Landsat 8 Operational Land Imager (OLI). First we compare the RSP and OLI radiance measurements to AVIRIS since the spectral response of the multispectral instruments can be used to synthesize a spectrally equivalent signal from the imaging spectrometer data. We then explore a method that uses AVIRIS as a transfer between RSP and OLI to show that radiometric traceability of a satellite-based imager can be used to calibrate a radiometer despite differences in spectral channel sensitivities. This calibration transfer shows agreement within the uncertainty of both the various instruments for most spectral channels.

calibrating↗
NASA NTRS2013

Longitudinally Jointed Edge-wise Compression Honeycomb Composite Sandwich Coupon Testing and FE Analysis: Three Methods of Strain Measurement, and Comparison

Three means (i.e., typical foil strain gages, fiber optic sensors, and a digital image correlation (DIC) system) were implemented to measure strains on the back and front surfaces of a longitudinally jointed curved test article subjected to edge-wise compression testing, at NASA Goddard Space Flight Center, according to ASTM C364. The Pre-test finite element analysis (FEA) was conducted to assess ultimate failure load and predict strain distribution pattern throughout the test coupon. The predicted strain pattern contours were then utilized as guidelines for installing the strain measurement instrumentations. The strain gages and fiber optic sensors were bonded on the specimen at locations with nearly the same strain values, as close as possible to each other, so that, comparisons between the measured strains by strain gages and fiber optic sensors, as well as the DIC system are justified. The test article was loaded to failure (at approximately 38 kips), at the strain value of approximately 10,000mu epsilon As a part of this study, the validity of the measured strains by fiber optic sensors is examined against the strain gage and DIC data, and also will be compared with FEA predictions.

Farrokh, Babak↗