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A micro sun sensor is being developed for use on a Mars rover for the Mars Science Laboratory Mission. The micro sun sensor, which is basically a small pinhole camera, consists of a small mask with pinholes, placed on top of an image detector.
The complementary metal-oxide-semiconductor (CMOS) active pixel sensor (APS) technology has been developed over the past three years by NASA at the Jet Propulsion Laboratory, and has reached a level of performance comparable to CCDs with greatly increased functionality but at a very reduced power level.
Accurate characterization of the Earth's radiant energy is critical for many climate monitoring and weather forecasting applications. For example, groups at the NASA Langley Research Center rely on stable visible- and infrared-channel calibrations in order to understand the temporal/spatial distribution of hazardous storms, as determined from an automated overshooting convective top detection algorithm. Therefore, in order to facilitate reliable, climate-quality retrievals, it is important that consistent calibration coefficients across satellite platforms are made available to the remote sensing community, and that calibration anomalies are recognized and mitigated. One such anomaly is the infrared imager brightness temperature (BT) drift that occurs for some Geostationary Earth Orbit satellite (GEOsat) instruments near local midnight. Currently the Global Space-Based Inter-Calibration System (GSICS) community uses the hyperspectral Infrared Atmospheric Sounding Interferometer (IASI) sensor as a common reference to uniformly calibrate GEOsat IR imagers. However, the combination of IASI, which has a 21:30 local equator crossing time (LECT), and hyperspectral Atmospheric Infrared Sounder (AIRS; 01:30 LECT) observations are unable to completely resolve the GEOsat midnight BT bias. The precessing orbit of the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS), however, allows sampling of all local hours every 46 days. Thus, VIRS has the capability to quantify the BT midnight effect observed in concurrent GEOsat imagers. First, the VIRS IR measurements are evaluated for long-term temporal stability between 2002 and 2012 by inter-calibrating with Aqua-MODIS. Second, the VIRS IR measurements are assessed for diurnal stability by inter-calibrating with Meteosat-9 (Met-9), a spin-stabilized GEOsat imager that does not manifest any diurnal dependency. In this case, the Met-9 IR imager is first adjusted with the official GSICS calibration coefficients. Then VIRS is used as a diurnal calibration reference transfer to produce hourly corrections of GEOsat IR imager BT. For the 9 three-axis stabilized GEO imagers concurrent with VIRS, the midnight effect increased the BT on average by 0.5 K (11 microns) and 0.4 K (12 microns), with a peak at approx.01:00 local time. As expected, the spin-stabilized GEOsats revealed a smaller diurnal temperature cycle (mostly < 0.2 K) with inconsistent peak hours.
Fixed packed bed reactors are compact, require minimum power and maintenance to operate, and are highly reliable. These features make this technology a highly desirable unit operation for long duration life support systems in space. NASA is developing an ISS experiment to address this technology with particular focus on water reclamation and air revitalization. Earlier research and development efforts funded by NASA have resulted in two hydrodynamic models which require validation with appropriate instrumentation in an extended microgravity environment. To validate these models, the instantaneous distribution of the gas and liquid phases must be measured.Electrical Capacitance Volume Tomography (ECVT) is a non-invasive imaging technology recently developed for multi-phase flow applications. It is based on distributing flexible capacitance plates on the peripheral of a flow column and collecting real-time measurements of inter-electrode capacitances. Capacitance measurements here are directly related to dielectric constant distribution, a physical property that is also related to material distribution in the imaging domain. Reconstruction algorithms are employed to map volume images of dielectric distribution in the imaging domain, which is in turn related to phase distribution. ECVT is suitable for imaging interacting materials of different dielectric constants, typical in multi-phase flow systems. ECVT is being used extensively for measuring flow variables in various gas-liquid and gas-solid flow systems. Recent application of ECVT include flows in risers and exit regions of circulating fluidized beds, gas-liquid and gas-solid bubble columns, trickle beds, and slurry bubble columns. ECVT is also used to validate flow models and CFD simulations. The technology is uniquely qualified for imaging phase concentrations in packed bed reactors for the ISS flight experiments as it exhibits favorable features of compact size, low profile sensors, high imaging speed, and flexibility to fit around columns of various shapes and sizes. ECVT is also safer than other commonly used imaging modalities as it operates in the range of low frequencies (1 MHz) and does not radiate radioactive energy. In this effort, ECVT is being used to image flow parameters in a packed bed reactor for an ISS flight experiment.
The LST Fine Guidance Sensor design is shaped by the rate of occurrence of suitable guide stars, the competition for telescope focal plane space with the Science Instruments, and the sensitivity of candidate image motion sensors. The relationship between these parameters is presented, and sensitivity to faint stars is shown to be of prime importance. An interferometric technique of image motion sensing is shown to have improved sensitivity and, therefore, a reduced focal plane area requirement in comparison with other candidate techniques (image-splitting prism and image dissector tube techniques). Another design requirement is speed in acquiring the guide star in order to maximize the time available for science observations. The design constraints are shown parametrically, and modelling results are presented.
The newly available ns-gated laser-entrance-hole (LEH) imager on the National Ignition Facility provides routine, non-perturbative measurements of the x-ray emission from laser-heated plasmas inside the hohlraum as viewed at 19° to the hohlraum axis through one of its LEHs. Multiple images are acquired for a series of times and filter-selected x-ray energy bands within a single shot. The images provide time dependent data on phenomena including the effective radius of the LEH, the length of the gold-plasma “bubble” evolving off the interior wall surface heated by the outer beams, the evolving radius of the x-ray heated hohlraum wall, and the radius of the ablation front of the fusion capsule. Here, these measurements are explained and illustrated with sample data. These techniques are then applied to understand hohlraum behavior as a function of gas fill. For hohlraums with helium gas fill densities of 0.15 to 0.30 mg/cm 3 , synthetic images computed from simulations agree well with experimental gated LEH images when an inhibited heat transport model [Jones et al., Phys. Plasmas 24, 056312 (2017)] is used. This model can be adjusted to reproduce the expansion rate of the laser-heated plasma bubble in such a way as to improve agreement with the images. At the higher 0.6 mg/cc gas fill, the experimental images show more pronounced 3D features, resulting in slightly less good agreement with the 2D simulations.
Existing algorithms for Agile Earth Observing Satellites((Lemaitre et al. 2002)) were largely created for 1D line sensors that acquire images in linear swaths. However, imaging satellites increasingly use 2D framing sensors (cameras) that capture discrete rectangular images. We describe tiling step-stare approaches that are more suited to rectangular image footprints than are 1D swath-based algorithms. Optimal area planning for these 2D framing instruments is an NPcomplete problem and intractable for large areas, so we present four approximation algorithms. Strategies are compared against a prior 2D framing instrument algorithm (Knight 2014) in three computational experiments. The impact of observer agility on schedule makespan is examined. Makespans vary more as observer agility decreases toward a critical point, then vary less after the critical point, suggesting a possible problem phase transition.
The Thermal Infrared Sensor-2 (TIRS-2) scheduled to launch in December 2020 aboard Landsat 9 will continue Landsat's four decade-long legacy of providing moderate resolution thermal imagery from low earth orbit (at 705 km) for environmental applications. Like the Thermal Infrared Sensor aboard Landsat 8, it is a pushbroom sensor with a cross-track field of view of 15 and provides two spectral channels at 10.8 and 12 micrometers. To ensure radiometric, spatial, and spectral performance, a comprehensive pre-launch testing program is being conducted at NASA Goddard Space Flight Center at the component, subsystem, and instrument level. This effort will focus on the results from the subsystem level testing to assess TIRS-2 imaging performance including focus, spatial performance, and stray light rejection. It is also used to provide a preliminary assessment of spectral performance. The TIRS-2 subsystem is placed in a thermal vacuum chamber with the calibration ground support equipment, which provides a flexible blackbody illumination source and optics to assess imaging performance. Spectral performance is tested using a spectral response test setup with its own illumination source outside the chamber that propagates through the calibration ground support equipment in an optical configuration designed for this purpose. The results show that TIRS-2 performance is expected to meet all of its performance requirements with few waivers and deviations.
Passive microwave data have been used to infer the snow-covered area and snow water equivalent (SWE) over forested areas, but the accuracy of these retrieved snow parameters cannot be easily validated for heterogeneous vegetated regions. The Boreal Ecosystem-Atmosphere Study Winter Field Campaign provided the opportunity to study the effect of boreal forests on snow parameter retrieval in detail. Microwave radiometers (18, 37, and 92 GHz) were flown on board the Canadian National Aeronautical Establishment's Twin Otter. Flight lines covered both the southern study area near Prince Albert and the northern study area near Thompson, Canada. During the 1994 winter campaign, extensive ground-based snow cover information, including depth, density, and grain size, was collected along most of the flight lines, jointly by U.S. and Canadian investigators. Satellite data collected by the special sensor microwave imager are also used for comparison. Preliminary results reconfirmed the relationship between microwave brightness temperature and SWE. However, the effect of forest cover observed by the aircraft sensors is different from that of the satellite observations. This is probably due to the difference in footprint averaging. There were also several flight lines flown over Candle Lake and Waskesiu Lake to assess lake ice signatures. Preliminary results show the thickness of the lake ice may be inferred from the airborne microwave observations. The microwave signature relationship between lake ice and snow matches the results from radiative transfer calculations.
The interpretation of satellite data is reviewed to address the possibility of extracting geophysically useful data regarding ice and snow. The scientific and practical utility of such data is examined in terms of the required and available scales, resolutions, and data types. Satellite instrumentation for ice and snow studies includes the AVHRR, the Special Sensor Microwave Imager, and the altimeters on Geosat and the European Remote Sensing Satellite. The satellites are presently used for conducting investigations of the microwave radiometry of snow, shortwave snowcover inventories, and sensor and model validations. It is noted that these studies encompass a range of ice properties and employ approaches and scientists from a number of fields. Areas that remain to be addressed in the field include snow structure and substrate effects, fall cooling, floe flooding, and brine expulsion.
This paper gives the status of theoretical and experimental efforts at JPL in the development of environmentally robust (radiation hard and radiation tolerant), ultra-low power, high performance CMOS active pixel sensor (APS) imagers for star tracker/imager applications.
The combined effects of imaging gathering, sampling and reconstruction are analyzed in terms of image fidelity. The analysis is based upon a standard end-to-end linear system model which is sufficiently general so that the results apply to most line-scan and sensor-array imaging systems. Shift-variant sampling effects are accounted for with an expected value analysis based upon the use of a fixed deterministic input scene which is randomly shifted (mathematically) relative to the sampling grid. This random sample-scene phase approach has been used successfully by the author and associates in several previous related papers.
The characteristics of a quadrant-CCD designed for pointing and tracking are discussed with reference to its use in an adaptive optics program. The quadrant-CCD is used to correct stellar image motion proceeding from atmospheric turbulence by means of a system in which a sensor measures the image offset and sends data to a high-speed tip/tilt mirror. The design and control of the device are detailed, including four 100-micron-square pixels, the quadrant architecture, controller electronics, and data acquisition computer and interface. The transfer function is set forth in the x and y directions, and transfer curves are shown. A laboratory simulation of random image motion was conducted to evaluate the performance of the quadrant-CCD as an image motion sensor, and the experimental results are presented. The suitability of the quadrant-CCD for space-based pointing and tracking uses is demonstrated by this test and two earlier theoretical studies. Some future developments which improve performance capabilities are mentioned.
No abstract available
NASA has a continuing requirement to collect high-quality in situ data for the vicarious calibration of current and next generation ocean color satellite sensors and to validate the algorithms that use the remotely sensed observations. Recent NASA airborne missions over Monterey Bay, CA, have demonstrated novel above- and in-water measurement capabilities supporting a combined airborne sensor approach (imaging spectrometer, microradiometers, and a sun photometer). The results characterize coastal atmospheric and aquatic properties through an end-to-end assessment of image acquisition, atmospheric correction, algorithm application, plus sea-truth observations from state-of-the-art instrument systems. The primary goal is to demonstrate the following in support of calibration and validation exercises for satellite coastal ocean color products: 1) the utility of a multi-sensor airborne instrument suite to assess the bio-optical properties of coastal California, including water quality; and 2) the importance of contemporaneous atmospheric measurements to improve atmospheric correction in the coastal zone. The imaging spectrometer (Headwall) is optimized in the blue spectral domain to emphasize remote sensing of marine and freshwater ecosystems. The novel airborne instrument, Coastal Airborne In-situ Radiometers (C-AIR) provides measurements of apparent optical properties with high dynamic range and fidelity for deriving exact water leaving radiances at the land-ocean boundary, including radiometrically shallow aquatic ecosystems. Simultaneous measurements supporting empirical atmospheric correction of image data are accomplished using the Ames Airborne Tracking Sunphotometer (AATS-14). Flight operations are presented for the instrument payloads using the Center for Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter flown over Monterey Bay during the seasonal fall algal bloom in 2011 (COAST) and 2013 (OCEANIA) to support bio-optical measurements of phytoplankton for coastal zone research.
In anticipation of the launch of the Earth Observing System (EOS) Terra, and the PM-1 spacecraft in 1999 and 2000, respectively, efforts are ongoing to determine errors of satellite-derived snow-cover maps. EOS Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer-E (AMSR-E) snow-cover products will be produced. For this study we compare snow maps covering the same study area acquired from different sensors using different snow- mapping algorithms. Four locations are studied: 1) southern Saskatchewan; 2) a part of New England (New Hampshire, Vermont and Massachusetts) and eastern New York; 3) central Idaho and western Montana; and 4) parts of North and South Dakota. Snow maps were produced using a prototype MODIS snow-mapping algorithm used on Landsat Thematic Mapper (TM) scenes of each study area at 30-m and when the TM data were degraded to 1 -km resolution. National Operational Hydrologic Remote Sensing Center (NOHRSC) 1 -km resolution snow maps were also used, as were snow maps derived from 1/2 deg. x 1/2 deg. resolution Special Sensor Microwave Imager (SSM/1) data. A land-cover map derived from the International Geosphere-Biosphere Program (IGBP) land-cover map of North America was also registered to the scenes. The TM, NOHRSC and SSM/I snow maps, and land-cover maps were compared digitally. In most cases, TM-derived maps show less snow cover than the NOHRSC and SSM/I maps because areas of incomplete snow cover in forests (e.g., tree canopies, branches and trunks) are seen in the TM data, but not in the coarser-resolution maps. The snow maps generally agree with respect to the spatial variability of the snow cover. The 30-m resolution TM data provide the most accurate snow maps, and are thus used as the baseline for comparison with the other maps. Comparisons show that the percent change in amount of snow cover relative to the 3 0-m resolution TM maps is lowest using the TM I -km resolution maps, ranging from 0 to 40%. The highest percent change (less than 100%) is found in the New England study area, probably due to the presence of patchy snow cover. A scene with patchy snow cover is more difficult to map accurately than is a scene with a well-defined snowline such as is found on the North and South Dakota scene where the percent change ranged from 0 to 40%. There are also some important differences in the amount of snow mapped using the two different SSM/I algorithms because they utilize different channels.
Texture is known to be important in the analysis of radar images for geologic applications. It has previously been shown that texture features derived from the grey level co-occurrence matrix (GLCM) can be used to separate large scale texture in radar images. Here the influence of sensor parameters, specifically the spatial and radiometric resolution and flight parameters, i.e., the orientation of the surface structure relative to the sensor, on the ability to classify texture based on the GLCM features is investigated. It was found that changing these sensor and flight parameters greatly affects the usefulness of the GLCM for classifying texture on radar images.
Texture is known to be important in the analysis of radar images for geologic applications. It has previously been shown that texture features derived from the grey level co-occurrence matrix (GLCM) can be used to separate large scale texture in radar images. Here the influence of sensor parameters, specifically the spatial and radiometric resolution and flight parameters, i.e., the orientation of the surface structure relative to the sensor, on the ability to classify texture based on the GLCM features is investigated. It was found that changing these sensor and flight parameters greatly affects the usefulness of the GLCM for classifying texture on radar images.