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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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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Viking adaptive mission sequence and control operations

Viking mission operations were required to provide an adaptive sequencing capability in which future observations could be influenced by the latest information about Mars as it was obtained and analyzed. The mission operations strategy that was developed met this requirement and provided the capability to respond smoothly and efficiently to spacecraft subsystem anomalies with minimum impact on the science data gathering process. A description of the major elements of this adaptive man-in-the-loop control system is provided. Specific cases showing how it was utilized to enhance scientific return and to respond to spacecraft anomalies are also provided.

Larman, B. T.↗
NASA NTRS1983

The Galileo spacecraft system design

The Galileo Orbiter differs markedly from its Mariner, Viking and Voyager predecessors in many aspects of its design, as dictated by its unique mission characteristics. Novel design features include a dual spin configuration, long life bipropellant propulsion, radioisotope thermoelectric generators, and a star scanner. Other major changes are related to Space Shuttle Orbiter compatibility. The selection of a distributed data system employing a high speed data bus represents a major advance over Voyager systems. The command, control and data handling functions for the Orbiter are merged into a single software-controlled subsystem. The paramount importance of software development in the design of Galileo subsystems is noted, in view of the requirement for total engineering and science data acquisition process reprogrammability.

Jones, C. P.↗
NASA NTRS1983

The IRAS project organisation and mission operations

The project organisation of IRAS is described, showing the tasks assigned to each project group during post-launch operations. The satellite is described, emphasizing the detectors. In the task division, the role of the U.S. is to construct the telescope and survey instrument, launch the satellite, process final science data for the survey instrument, and provide certain standard satellite items. The Netherlands construct the spacecraft and three additional instruments, integrates and tests the overall satellite, and designs and participates in the development of the operational system. The U.K. provides the operational control center and primary tracking station, generates a system for preliminary science analysis of the survey data, provides housekeeping analysis software and science data distribution software, and staffs the control center operations. The teams involved in mission planning and operations, and their roles, are identified, and a block diagram of the operations organisation is presented.

Van Holtz, R. C.↗
NASA NTRS1999

Earth Orbiter 1: Wideband Advanced Recorder and Processor (WARP)

An advanced on-board spacecraft data system component is presented. The component is computer-based and provides science data acquisition, processing, storage, and base-band transmission functions. Specifically, the component is a very high rate solid state recorder, serving as a pathfinder for achieving the data handling requirements of next-generation hyperspectral imaging missions.

Smith, Terry↗
NASA NTRS1999

Earth Orbiter 1: Wideband Advanced Recorder and Processor (WARP)

An advanced on-board spacecraft data system component is presented. The component is computer-based and provides science data acquisition, processing, storage, and base-band transmission functions. Specifically, the component is a very high rate solid state recorder, serving as a pathfinder for achieving the data handling requirements of next-generation hyperspectral imaging missions.

Smith, Terry↗
NASA NTRS2004

The Spitzer science operations system : how well are we really doing?

This paper will describe how the SIRTF Science Operation System has performed since launch, and how the system has been adapted based upon in-flight performance. It will also discuss lessons learned which can be applied to future science operation systems. This work was performed at the California Institute of Technology under contract to the National Aeronautics and Space Administration.

Spitzer Space Telescope↗
NASA NTRS2007

Gravity Probe B Timing System and Roll Phase Determination

An oven-controlled crystal oscillator at 16.368 MHz provides clock signals to all GP-B components and synchronizes the data collection, transmission and processing. The sampled science data signals are stamped with the vehicle time, a counter of the 10Hz data strobe divided down from the clock. The GPS receiver supplies an external reference for time transfer between the vehicle time and coordinated universal time. Ground and space flight tests show the time transfer error is within 1 microsecond. The time latency between the effective sample time of science signals and the stamped vehicle time is verified to 1 ms in the ground tests. The GP-B satellite is controlled to roll with a period of 77.5 sec about an axis along the direction to the guide star to average out the disturbance torques fixed to the body of the satellite and reduce the gyroscope readout noise. The roll phase is determined on the ground to high accuracy with the telemetry data from two star trackers and used in the data analysis to separate the drifts of gyroscope spin axes in the orbital plane and perpendicular to the orbital plane. The flight data shows that the roll phase is controlled to within 40 arcsec with a measurement uncertainty of 7 arcsec.

Jie, Li↗
NASA NTRS2008

Comparison of Terra and Aqua MODIS VIS Bands On-Orbit Response

The Moderate Resolution Imaging Spectroradiometer (MODIS) has 36 spectral bands with a total of 490 detectors, covering spectral regions in the visible (VIS), near-infrared (NIR), short-wave infrared (SWIR), mid-wave infrared (MWIR), and long-wave infrared (LWIR). MODIS is a cross-track scanning radiometer which collects data using a rotating scan mirror (both sides) over a wide range of scan angles. The VIS, NIR, and SWIR bands (bands 1-19 and 26) make measurements of daytime surface reflected radiances, thus are referred to as the reflective solar bands (RSB). MODIS was built with a complete set of on-board calibrators, capable of providing radiometric, spatial, and spectral calibration and characterization during its entire mission. The RSB on-orbit calibration is primarily provided using a solar diffuser (SD) and a solar diffuser stability monitor (SDSM). The SD and SDSM calibration system is operated on a regular (weekly to bi-weekly) basis. The spectro-radiometric calibration assembly (SRCA) is another on-hoard calibrator that also provides RSB radiometric calibration support. For this purpose, the SRCA is operated in a radiometric mode on a monthly basis. A complete SRCA radiometric calibration is performed using different lamp configurations, or different radiance levels, to cover the range of RSB gain. Two additional SRCA modes with slightly different configurations are designed and operated for sensor on-orbit spectral and spatial characterization. In addition to its on-hoard calibrators, each MODIS makes monthly lunar observations to monitor RSB radiometric calibration stability. The MODIS lunar observations are made through its space view (SV) port at nearly the same lunar phase angles via spacecraft roll maneuvers. The SD, SRCA, and lunar measurements are made at different scan angles and data samples are collected for all spectral bands and detectors using both sides of the scan minor. Since launch, Terra and Aqua MODIS have operated successfully for more than 8 years and 6 years, respectively. Many SD/SDSM, SRCA, and lunar observations have been made by each instrument and used to derive RSB on-orbit calibration parameters, enabling corrections for sensor response changes and changes of the response versus scan angle (RVS). In general, the RSB calibration parameters are updated regularly into the MODIS Level 1B (LIB) code in support of continuous data processing for all MODIS science data products. This paper provides a brief description of MODIS RSB calibration methodologies and approaches, and summarizes on-orbit changes of their responses (gains), particularly for the VIS spectral bands.

Xiong, Xiaoxiong↗
NASA NTRS2012

Content Platforms Meet Data Storage, Retrieval Needs

Earth is under a constant barrage of information from space. Whether from satellites orbiting our planet, spacecraft circling Mars, or probes streaking toward the far reaches of the Solar System, NASA collects massive amounts of data from its spacefaring missions each day. NASA s Earth Observing System (EOS) satellites, for example, provide daily imagery and measurements of Earth s atmosphere, oceans, vegetation, and more. The Earth Observing System Data and Information System (EOSDIS) collects all of that science data and processes, archives, and distributes it to researchers around the globe; EOSDIS recently reached a total archive volume of 4.5 petabytes. Try to store that amount of information in your standard, four-drawer file cabinet, and you would need 90 million to get the job done. To manage the flood of information, NASA has explored technologies to efficiently collect, archive, and provide access to EOS data for scientists today and for years to come. One such technology is now providing similar capabilities to businesses and organizations worldwide.

Source record↗
NASA NTRS2015

Shearlet Features for Registration of Remotely Sensed Multitemporal Images

We investigate the role of anisotropic feature extraction methods for automatic image registration of remotely sensed multitemporal images. Building on the classical use of wavelets in image registration, we develop an algorithm based on shearlets, a mathematical generalization of wavelets that offers increased directional sensitivity. Initial experimental results on LANDSAT images are presented, which indicate superior performance of the shearlet algorithm when compared to classical wavelet algorithms.

Science data processing↗
NASA NTRS2016

High Resolution Image Reconstruction from Projection of Low Resolution Images DIffering in Subpixel Shifts

In this paper, we demonstrate a simple algorithm that projects low resolution (LR) images differing in subpixel shifts on a high resolution (HR) also called super resolution (SR) grid. The algorithm is very effective in accuracy as well as time efficiency. A number of spatial interpolation techniques using nearest neighbor, inverse-distance weighted averages, Radial Basis Functions (RBF) etc. used in projection yield comparable results. For best accuracy of reconstructing SR image by a factor of two requires four LR images differing in four independent subpixel shifts. The algorithm has two steps: i) registration of low resolution images and (ii) shifting the low resolution images to align with reference image and projecting them on high resolution grid based on the shifts of each low resolution image using different interpolation techniques. Experiments are conducted by simulating low resolution images by subpixel shifts and subsampling of original high resolution image and the reconstructing the high resolution images from the simulated low resolution images. The results of accuracy of reconstruction are compared by using mean squared error measure between original high resolution image and reconstructed image. The algorithm was tested on remote sensing images and found to outperform previously proposed techniques such as Iterative Back Projection algorithm (IBP), Maximum Likelihood (ML), and Maximum a posterior (MAP) algorithms. The algorithm is robust and is not overly sensitive to the registration inaccuracies.

0↗
NASA NTRS2016

A Survey of Cost Estimating Methodologies for Distributed Spacecraft Missions

Satellite constellations present unique capabilities and opportunities to Earth orbiting and near-Earth scientific and communications missions, but also present new challenges to cost estimators. An effective and adaptive cost model is essential to successful mission design and implementation, and as Distributed Spacecraft Missions (DSM) become more common, cost estimating tools must become more representative of these types of designs. Existing cost models often focus on a single spacecraft and require extensive design knowledge to produce high fidelity estimates. Previous research has examined the shortcomings of existing cost practices as they pertain to the early stages of mission formulation, for both individual satellites and small satellite constellations. Recommendations have been made for how to improve the cost models for individual satellites one-at-a-time, but much of the complexity in constellation and DSM cost modeling arises from constellation systems level considerations that have not yet been examined. This paper constitutes a survey of the current state-of-the-art in cost estimating techniques with recommendations for improvements to increase the fidelity of future constellation cost estimates. To enable our investigation, we have developed a cost estimating tool for constellation missions. The development of this tool has revealed three high-priority weaknesses within existing parametric cost estimating capabilities as they pertain to DSM architectures: design iteration, integration and test, and mission operations. Within this paper we offer illustrative examples of these discrepancies and make preliminary recommendations for addressing them. DSM and satellite constellation missions are shifting the paradigm of space-based remote sensing, showing promise in the realms of Earth science, planetary observation, and various heliophysical applications. To fully reap the benefits of DSM technology, accurate and relevant cost estimating capabilities must exist; this paper offers insights critical to the future development and implementation of DSM cost estimating tools.

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NASA NTRS2016

A Survey of Cost Estimating Methodologies for Distributed Spacecraft Missions

Satellite constellations and Distributed Spacecraft Mission (DSM) architectures offer unique benefits to Earth observation scientists and unique challenges to cost estimators. The Cost and Risk (CR) module of the Tradespace Analysis Tool for Constellations (TAT-C) being developed by NASA Goddard seeks to address some of these challenges by providing a new approach to cost modeling, which aggregates existing Cost Estimating Relationships (CER) from respected sources, cost estimating best practices, and data from existing and proposed satellite designs. Cost estimation through this tool is approached from two perspectives: parametric cost estimating relationships and analogous cost estimation techniques. The dual approach utilized within the TAT-C CR module is intended to address prevailing concerns regarding early design stage cost estimates, and offer increased transparency and fidelity by offering two preliminary perspectives on mission cost. This work outlines the existing cost model, details assumptions built into the model, and explains what measures have been taken to address the particular challenges of constellation cost estimating. The risk estimation portion of the TAT-C CR module is still in development and will be presented in future work. The cost estimate produced by the CR module is not intended to be an exact mission valuation, but rather a comparative tool to assist in the exploration of the constellation design tradespace. Previous work has noted that estimating the cost of satellite constellations is difficult given that no comprehensive model for constellation cost estimation has yet been developed, and as such, quantitative assessment of multiple spacecraft missions has many remaining areas of uncertainty. By incorporating well-established CERs with preliminary approaches to approaching these uncertainties, the CR module offers more complete approach to constellation costing than has previously been available to mission architects or Earth scientists seeking to leverage the capabilities of multiple spacecraft working in support of a common goal.

0↗
NASA NTRS2016

Trade-Space Analysis Tool for Constellations (TAT-C)

Traditionally, space missions have relied on relatively large and monolithic satellites, but in the past few years, under a changing technological and economic environment, including instrument and spacecraft miniaturization, scalable launchers, secondary launches as well as hosted payloads, there is growing interest in implementing future NASA missions as Distributed Spacecraft Missions (DSM). The objective of our project is to provide a framework that facilitates DSM Pre-Phase A investigations and optimizes DSM designs with respect to a-priori Science goals. In this first version of our Trade-space Analysis Tool for Constellations (TAT-C), we are investigating questions such as: How many spacecraft should be included in the constellation? Which design has the best costrisk value? The main goals of TAT-C are to: Handle multiple spacecraft sharing a mission objective, from SmallSats up through flagships, Explore the variables trade space for pre-defined science, cost and risk goals, and pre-defined metrics Optimize cost and performance across multiple instruments and platforms vs. one at a time.This paper describes the overall architecture of TAT-C including: a User Interface (UI) interacting with multiple users - scientists, missions designers or program managers; an Executive Driver gathering requirements from UI, then formulating Trade-space Search Requests for the Trade-space Search Iterator first with inputs from the Knowledge Base, then, in collaboration with the Orbit Coverage, Reduction Metrics, and Cost Risk modules, generating multiple potential architectures and their associated characteristics. TAT-C leverages the use of the Goddard Mission Analysis Tool (GMAT) to compute coverage and ancillary data, streamlining the computations by modeling orbits in a way that balances accuracy and performance.TAT-C current version includes uniform Walker constellations as well as Ad-Hoc constellations, and its cost model represents an aggregate model consisting of Cost Estimating Relationships (CERs) from widely accepted models. The Knowledge Base supports both analysis and exploration, and the current GUI prototype automatically generates graphics representing metrics such as average revisit time or coverage as a function of cost.

Science Data Processing↗
NASA NTRS2016

Streamlining the Design Tradespace for Earth Imaging Constellations

Satellite constellations and Distributed Spacecraft Mission (DSM) architectures offer unique benefits to Earth observation scientists and unique challenges to cost estimators. The Cost and Risk (CR) module of the Tradespace Analysis Tool for Constellations (TAT-C) being developed by NASA Goddard seeks to address some of these challenges by providing a new approach to cost modeling, which aggregates existing Cost Estimating Relationships (CER) from respected sources, cost estimating best practices, and data from existing and proposed satellite designs. Cost estimation through this tool is approached from two perspectives: parametric cost estimating relationships and analogous cost estimation techniques. The dual approach utilized within the TAT-C CR module is intended to address prevailing concerns regarding early design stage cost estimates, and offer increased transparency and fidelity by offering two preliminary perspectives on mission cost. This work outlines the existing cost model, details assumptions built into the model, and explains what measures have been taken to address the particular challenges of constellation cost estimating. The risk estimation portion of the TAT-C CR module is still in development and will be presented in future work. The cost estimate produced by the CR module is not intended to be an exact mission valuation, but rather a comparative tool to assist in the exploration of the constellation design tradespace. Previous work has noted that estimating the cost of satellite constellations is difficult given that no comprehensive model for constellation cost estimation has yet been developed, and as such, quantitative assessment of multiple spacecraft missions has many remaining areas of uncertainty. By incorporating well-established CERs with preliminary approaches to approaching these uncertainties, the CR module offers more complete approach to constellation costing than has previously been available to mission architects or Earth scientists seeking to leverage the capabilities of multiple spacecraft working in support of a common goal.

Science Data Processing↗