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Cost estimates for both the on-board and ground segments of the Space Station Data System (SSDS) are presented along with summary program schedules. Advanced technology development recommendations are provided in the areas of distributed data base management, end-to-end protocols, command/resource management, and flight qualified artificial intelligence machines.
A program installed in the ATSOCC on-line computer operates with attitude sensor data to produce a smoothed real-time orbit estimate. This estimate is obtained from a Kalman filter which enables the estimate to be maintained in the absence of T/M data. The results are described of analytical and numerical investigations into the sensitivity of Control Center output to the position errors resulting from the real-time estimation. The results of the numerical investigation, which used several segments of ATS-6 data gathered during the Sensor Data Acquisition run on August 19, 1974, show that the implemented system can achieve absolute position determination with an error of about 100 km, implying pointing errors of less than 0.2 deg in latitude and longitude. This compares very favorably with ATS-6 specifications of approximately 0.5 deg in latitude-longitude.
Differential deposition corrects the low- and mid- spatial-frequency deviations in the axial figure of Wolter-type grazing incidence X-ray optics. Figure deviations is one of the major contributors to the achievable angular resolution. Minimizing figure errors can significantly improve the imaging quality of X-ray optics. Material of varying thickness is selectively deposited, using DC magnetron sputtering, along the length of optic to minimize figure deviations. Custom vacuum chambers are built that can incorporate full-shell and segmented Xray optics. Metrology data of preliminary corrections on a single meridian of full-shell x-ray optics show an improvement of mid-spatial frequencies from 6.7 to 1.8 arc secs HPD. Efforts are in progress to correct a full-shell and segmented optics and to verify angular-resolution improvement with X-ray testing.
An unsupervised clustering algorithm is used to segment multifrequency polarimetric radar data from the NASA/JPL airborne SAR (synthetic aperture radar). Twenty-two parameters are evaluated for their discriminatory capability for each pixel of an image. A clustering analysis is then performed using different subsets of these parameters. This analysis relies on data taken as part of an intensive field experiment during the summer of 1988 in the vicinity of the Pisgah lava flow in the Mojave Desert in southern California. As part of the experiment, extensive ground truth was acquired, including dielectric constant and topography measurements. Segmentation results show good agreement with these measurements.
Dynamic loads were investigated to provide simulation and analysis of the space shuttle orbiter digital data processing system (DDPS). Segments of the ascent test (OFT) configuration were modeled utilizing the information management system interpretive model (IMSIM) in a computerized simulation modeling of the OFT hardware and software workload. System requirements for simulation of the OFT configuration were defined, and sensitivity analyses determined areas of potential data flow problems in DDPS operation. Based on the defined system requirements and these sensitivity analyses, a test design was developed for adapting, parameterizing, and executing IMSIM, using varying load and stress conditions for model execution. Analyses of the computer simulation runs are documented, including results, conclusions, and recommendations for DDPS improvements.
A multiple high-order derivative analysis algorithm has been developed which can automatically extract absorption band positions from low-quality reflectance spectra with little degredation of accuracy. Overlapping bands with comparable widths and intensities can be resolved whose centers are as close as 0.3-0.5 W, with safer resolution limits of 0.6-1.0 W band center separations suggested for overlapping bands that are dissimilar. The segment length for smoothing is continually adjusted to about 0.5 W to minimize signal distortion, and a spectral pattern recognition algorithm predicts the signal spectrum and calculates approximate W across the spectrum using its second derivative. A single-pass cubic spline is applied to the smoothed data, and a sliding segment sixth-order polynomial is fit to the spectrum, with the length of the segment being continuously locally adjusted to 1.0 W across the spectrum. Good reliability and consistency of the algorithm is demonstrated with application to laboratory and earth-based telescope spectra.
The performance, design, development, and test requirements for an optical mass data storage and retrieval system prototype (AMM-13) are established. This system interfaces to other system segments of the NASA End-to-End Data System via the Data Base Management System segment and is designed to have a storage capacity of 10 to the 13th power bits (10 to the 12th power bits on line). The major functions of the system include control, input and output, recording of ingested data, fiche processing/replication and storage and retrieval.
Rockster-MER is an autonomous perception capability that was uploaded to the Mars Exploration Rover Opportunity in December 2009. This software provides the vision front end for a larger software system known as AEGIS (Autonomous Exploration for Gathering Increased Science), which was recently named 2011 NASA Software of the Year. As the first step in AEGIS, Rockster-MER analyzes an image captured by the rover, and detects and automatically identifies the boundary contours of rocks and regions of outcrop present in the scene. This initial segmentation step reduces the data volume from millions of pixels into hundreds (or fewer) of rock contours. Subsequent stages of AEGIS then prioritize the best rocks according to scientist- defined preferences and take high-resolution, follow-up observations. Rockster-MER has performed robustly from the outset on the Mars surface under challenging conditions. Rockster-MER is a specially adapted, embedded version of the original Rockster algorithm ("Rock Segmentation Through Edge Regrouping," (NPO- 44417) Software Tech Briefs, September 2008, p. 25). Although the new version performs the same basic task as the original code, the software has been (1) significantly upgraded to overcome the severe onboard re source limitations (CPU, memory, power, time) and (2) "bulletproofed" through code reviews and extensive testing and profiling to avoid the occurrence of faults. Because of the limited computational power of the RAD6000 flight processor on Opportunity (roughly two orders of magnitude slower than a modern workstation), the algorithm was heavily tuned to improve its speed. Several functional elements of the original algorithm were removed as a result of an extensive cost/benefit analysis conducted on a large set of archived rover images. The algorithm was also required to operate below a stringent 4MB high-water memory ceiling; hence, numerous tricks and strategies were introduced to reduce the memory footprint. Local filtering operations were re-coded to operate on horizontal data stripes across the image. Data types were reduced to smaller sizes where possible. Binary- valued intermediate results were squeezed into a more compact, one-bit-per-pixel representation through bit packing and bit manipulation macros. An estimated 16-fold reduction in memory footprint relative to the original Rockster algorithm was achieved. The resulting memory footprint is less than four times the base image size. Also, memory allocation calls were modified to draw from a static pool and consolidated to reduce memory management overhead and fragmentation. Rockster-MER has now been run onboard Opportunity numerous times as part of AEGIS with exceptional performance. Sample results are available on the AEGIS website at http://aegis.jpl.nasa.gov.
The field deployment phase of NASA’s Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) took place around the Philippines during August–October 2019, with the primary goal of jointly investigating aerosols and tropical meteorology at the micro-β to meso-β scales. A suite of instruments was deployed on NASA’s P-3B Orion aircraft to accomplish this mission, including: the Advanced Microwave Precipitation Radiometer (AMPR), Airborne Precipitation and cloud Radar 3rd Generation (APR-3), High Spectral Resolution Lidar 2 (HSRL2), and Advanced Vertical Atmospheric Profiling System (AVAPS) dropsondes. To examine potential aerosol influences on maritime tropical convection, P-3 flight segments throughout CAMP2Ex were binned into similar environmental groups using “low,” “medium,” and “high” values of nine AVAPS-derived parameters with known physical connections to convective frequency and/or intensity. Aerosol concentrations in each flight segment were evaluated using three HSRL2 variables at 355 and 532 nm: aerosol backscatter, aerosol extinction, and aerosol optical thickness. A set of radiometer- and radar-derived variables directly related to convective frequency and/or intensity was used to characterize convection, which included: AMPR-derived integrated cloud liquid water; polarization-corrected temperatures at 10.7, 19.35, 37.1, and 85.5 GHz; peak equivalent radar reflectivity factor (ZH); peak height of 30-dBZ ZH; and the number of radar data columns with composite ZH > 30 dBZ. The ZH analyses were performed using both Ku- and Ka-band APR-3 data. For each flight segment, correlation coefficients were calculated between each convective parameter and aerosol concentrations within the “low,” “medium,” and “high” groups for each environmental variable. The environmental stratification thresholds were then varied in a series of sensitivity tests. Several noteworthy correlations were observed between the convective and aerosol parameters within the environmental groups, especially when stratifying the environments based on their 850–500-hPa temperature lapse rate, 700–500-hPa temperature lapse rate, and K-Index. The convective parameters were often correlated most strongly with 355-nm extinction, 532-nm extinction, and 532-nm backscatter, while the presence of precipitation-sized liquid and ice hydrometeors contributed to some unexpected negative correlations. In general, as environmental conditions became more favorable for convection, a stronger correlation was observed between the convective parameters and aerosol concentrations. However, a “Goldilocks” zone of medium aerosol concentration was correlated most strongly with the convective parameters in many cases. These results stress the importance of considering environmental and aerosol conditions together when evaluating their impacts on convection. This presentation will provide a detailed discussion of these results and their implications, a summary of the limitations associated with such an analysis, and suggestions for future work.
An evaluation of suitable edge discrimination techniques and their application to image segmentation is reported. From an analysis of Thematic Mapper Simulator data, it is concluded that segmentation by automated edge discrimination is a valuable technique which can be used in the development of per-field classifiers. A Laplacian convolution operator appears to be the most cost-effective high-pass filter. Spatial frequency domain filtering is more versatile in its ability to enhance different edge types. A simple global gray value threshold can produce good edge discrimination from an enhanced image which may be improved by using a local thresholding technique. A gap-fill postprocessing technique is necessary for useful segmentation. Gradient and other directionally dependent techniques are unsuitable for segmentation.
Soil moisture variations have a straightforward impact on overlying air temperatures, wetter soils can induce higher evaporative cooling of the soil and thus, locally, cooler temperatures overall. Not known, however, is the degree to which soil moisture variations can affect remote air temperatures through their impact on the atmospheric circulation. In this talk we describe a two-pronged analysis that addresses this question. In the first segment, an extensive ensemble of NASA/GSFC GEOS-5 atmospheric model simulations is analyzed statistically to isolate and quantify the contributions of various soil moisture states, both local and remote, to the variability of air temperature at a given local site. In the second segment, the relevance of the derived statistical relationships is evaluated by applying them to observations-based data. Results from the second segment suggest that the GEOS-5-based relationships do, at least to first order, hold in nature and thus may provide some skill to forecasts of air temperature at subseasonal time scales, at least in certain regions.
The naturally-occurring radionuclides protactinium-231 ( 231 Pa) and thorium-230 ( 230 Th) are produced at approximately uniform rates in the ocean and thought to be removed from the water column through a reversible exchange with settling particles. Recent measurements along the U.S. GEOTRACES North Atlantic transect (GA03) revealed two features which are at odds with current understanding about 231 Pa and 230 Th cycling in the ocean: (i) a sharp decrease in dissolved 231 Pa ( 231 Pa d ) and 230 Th ( 230 Th d ) activities with depth below 2000-4000 m and (ii) very high particulate 231 Pa ( 231 Pa p ) and 230 Th ( 230 Th p ) activities near the bottom, at a number of stations between the New England continental shelf and Bermuda. Concomitant measurements of light attenuation from beam transmissometry showed that both features occur in benthic nepheloid layers (BNLs), which suggests that these features may stem, at least partly, from the presence of resuspended sediment in the deep water column. Here we explore the behaviour of 231 Pa and 230 Th in BNLs by using (i) radionuclide, optical, and hydrographic data from the western segment of GA03 (west of Bermuda) and (ii) a simplified model of particle and radionuclide cycling that includes a lateral particle source. First, the BNLs observed at GA03 stations are characterized from measurements of the beam attenuation coefficient converted to particle concentrations. At all stations, particle concentrations below the clear water minimum were the highest in the bottom mixed layer, whose thickness ranged from 95 to 320 m, and decreased generally with height above the bottom. The thickness of strong BNLs varied from 482 to 1358 m and the vertical integral of particle concentration in excess to that at the clear water minimum varied from 1 x 10 4 to 2 x 10 6 mg m −2 , among different stations. Second, the particle-radionuclide model is fitted to data from stations GT11-04 (New England continental rise) and GT11-08 (Hatteras abyssal plain), where samples for radionuclide analyses were collected in the BNL. The model can reproduce simultaneously the increase of particle concentration with depth, the low 231 Pa d and 230 Th d in the BNLs, and the high 231 Pa p and 230 Th p near the bottom. According to the model, at heights less than about 300 m above the seafloor, the dissolved phase was set primarily by a balance between adsorption and desorption, with vertical turbulent mixing playing a secondary role, whilst the particulate phase behaved largely as a non-reactive constituent supplied laterally and transported vertically by particle settling and turbulent mixing. Sensitivity tests with the model suggest that lateral particle sources near continental slopes and similar reliefs can produce significant biases both in the 230 Th normalization method and in the interpretation of sediment 231 Pa/ 230 Th records. Our findings yield insights into the influence of sediment resuspension and transport on 231 Pa and 230 Th in the deep ocean and highlight the need for considering these processes in paleoceanographic applications.
Wildfire occurrences have been increasing for the past decade, leaving devastating traces across the world. In the recent efforts, remote sensing and airborne missions have been utilized to better understand and manage wildfires. This has resulted in an exponential increase in volume of remote sensing data, which has pushed the need for intelligent automation of data extraction for wildfire studies. Machine learning offers accurate automation in detecting such natural anomalies and enable decision-makers to take actions in a timely manner. Recent advances in machine learning algorithms, namely probabilistic generative methods, allow researchers and decisionmakers to step beyond detection and study “what-if” scenarios for wildfire occurrences. Additionally, they offer better imitations to the stochastic behavior of nature, and wildfire events. However, optimizing the performance of these probabilistic generative models is a computationally expensive process, specially using digital computers. On the other hand, quantum computers have recently shown a promise to reduce computationally costly training of such models and provide performance improvements. There is a body of research investigating the potential for improved machine learning methods in which key operations are performed on a quantum computer. In this study, we propose a probabilistic image-toimage segmentation approach combining a very well-known segmentation method, U-NET, with a Conditional Variational Auto-Encoder (CVAE) to not only detect wildfires but also describe the stochasticity of the phenomenon and be capable of running “what-if” scenarios. Our proposed model is compatible with training on quantum computers, which results in a quantum-assisted image-to-image segmentation approach and can be used to benchmark the potential benefit of quantum computing over the classical one.
Ion density and velocity measurements from the Dynamics Explorer 2 (DE 2) spacecraft are used to obtain the average magnetic local time versus invariant latitude distribution of irregularities in the high-latitude F region ionosphere. To study the small-scale structure and its relationship to background conditions in the ionosphere, we have formed a reduced database using 2-s (approx. = 16 km) segments of the ion density and velocity data. The background gradients associated with each 2-s segment and the spectral characteristics, such as power at 6 Hz (approx. = 1.3 km) and spectral index, are among the reduced parameters used in this study. The relationship between the observed plasma structure and its motion is complex and dependent on the externally applied fields as well as locally generated plasma structure. The evolution of plasma structures also depends critically on the conductivity of the underlying ionosphere. Observations indicate an enhancement of irregularity amplitudes in two spatially isolated regions in both the ion density and the velocity. Convective properties seem to play a more important role in winter hemisphere where smaller-scale structures are maintained outside the source regions. (Delta)V irregularity amplitudes are enhanced in the cusp and the polar cap during northward interplanetary magnetic field regardless of season. The power in (Delta)V is usually higher than that associated with local polarization electric fields, suggesting that the observed structure in (Delta)N/N is strongly influenced by (Delta)V structure applied to large density gradients.
Centerline noise measured during standard ILS and two-segment approaches in DC-8-61 aircraft were compared with noise predicted for these procedures using an existing noise prediction technique. Measured data is considered to be in good agreement with predicted data. Ninety EPNdB sideline locations were calculated from flight data obtained during two-segment approaches and were compared with predicted 90 EPNdB contours that were computed using three different models for excess ground attenuation and a contour with no correction for ground attenuation. The contour not corrected for ground attenuation was in better agreement with the measured data.
Experimental tests with diesel number 2 and Jet A fuels were conducted in a combustor segment to obtain comparative data on exhaust emissions and blowout limits. An air-atomizing nozzle was used to inject the fuels. Tests were also made with diesel number 2 fuel using a pressure-atomizing nozzle to determine the effectiveness of the air-atomizing nozzle in reducing exhaust emissions. Test conditions included fuel-air ratios of 0.008 to 0.018, inlet-air total pressures and temperatures of 41 to 203 newtons per square centimeter and 477 to 811 K, respectively, and a reference velocity of 21.3 meters per second. Smoke number and unburned hydrocarbons were twice as high with diesel number 2 as with Jet A fuel. This was attributed to diesel number 2 having a higher concentration of aromatics and lower volatility than Jet A fuel. Oxides of nitrogen, carbon monoxide, and blowout limits were approximately the same for the two fuels. The air-atomizing nozzle, as compared with the pressure-atomizing nozzle, reduced oxides-of-nitrogen by 20 percent, smoke number by 30 percent, carbon monoxide by 70 percent, and unburned hydrocarbons by 50 percent when used with diesel number 2 fuel.
The author has identified the following significant results. S190B imagery was the best single product from which fairly detailed structural and some lithologic mapping could be accomplished in the Big Horn basin, the Owl Creek Mountains, and the northern Big Horn Mountains. The Nye-Bowler lineament could not be extended east of its presently mapped location although a linear (fault or monocline) was noted that may be part of the lineament, but north of postulated extensions. Much more structure was discernible in the Big Horn basin than could be seen on LANDSAT-1 imagery; RB-57 color IR photography, in turn, revealed additional folds and faults. A number of linears, several of which could be identified as faults and one a monocline, cut obliquely the east-west trending Owl Creek uplift. The heavy forest cover of the Black Hills makes direct lithologic delineation impossible. However, drainage and linear overlays revealed differences in pattern between the areas of exposed Precambrian crystalline core and the flanking Paleozoic rocks. S192 data, even precision corrected segments, were not of much use.
The author has identified the following significant results. A conceptual man machine system framework was created for a large scale agricultural remote sensing system. The system is based on and can grow out of the local recognition mode of LACIE, through a gradual transition wherein computer support functions supplement and replace AI functions. Local proportion estimation functions are broken into two broad classes: (1) organization of the data within the sample segment; and (2) identification of the fields or groups of fields in the sample segment.