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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 397 records · Page 22
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NASA NTRS2018

On-Orbit Verification of GLM Navigation on GOES-16

The GOES-R flight project has developed the Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) to perform independent INR evaluations of the optical instruments on the GOES-R series spacecraft. In this presentation, we document the development of navigation (NAV) evaluation capabilities within IPATS for the Geostationary Lightning Mapper (GLM). We also discuss the post-processing quality filtering developed for GLM NAV, and present example results for several GLM background image datasets. Initial results suggest that GOES-16 GLM is compliant with navigation requirements.

GLM↗
NASA NTRS2018

On-Orbit Verification of GLM Navigation on GOES-16

The GOES-R flight project has developed the Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) to perform independent INR evaluations of the optical instruments on the GOES-R series spacecraft. In this paper, we document the development of navigation (NAV) evaluation capabilities within IPATS for the Geostationary Lightning Mapper (GLM). We also discuss the post-processing quality filtering developed for GLM NAV, and present example results for several GLM datasets. Initial results suggest that GOES-16 GLM is compliant with navigation requirements.

On-Orbit↗
NASA NTRS2018

Evaluation of Geostationary Lightning Mapper (GLM) Navigation Performance with the INR Performance Assessment Toolset (IPATS)

The GOES-R flight project has developed the Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) to perform independent INR evaluations of the optical instruments on the GOES-R series spacecraft. In this presentation, we document the development of navigation (NAV) evaluation capabilities within IPATS for the Geostationary Lightning Mapper (GLM). We also discuss the post-processing quality filtering developed for GLM NAV, and present example results for several GLM background image datasets. Initial results suggest that GOES-16 GLM is compliant with navigation requirements.

Isaacson, Peter J.↗
NASA NTRS2018

Deep Space Optical Communications (DSOC)

NASA’s future deep space science and exploration missions will require enhanced communications and navigation services. Laser communications offers expanded bandwidth and the potential for satisfying this need, with comparable mass and power as state of the art telecommunication systems. Consequently, NASA is planning a Deep Space Optical Communications (DSOC) technology demonstration, to retire the risk for future enhanced optical communication services. NASA’s upcoming Psyche Mission scheduled to launch in August of 2022 plans to host a DSOC flight laser transceiver (FLT) for demonstrating optical links from deep-space to earth. Existing ground assets retrofitted with laser transmitters and photon-counting receivers will be used for the technology demonstration. Advancing optical technology from near-Earth ranges to deep space (> 0.01 astronomical units or AU) involves orders of magnitude increased link difficulty (defined as data-rate squared distance). The plan to bridge the difficulty gap implements new technologies developed over the past two decades. These technologies emphasize high photon efficiency (HPE) with the use of high-peak-to-average power laser transmitters in space, and single photon counting sensitivity detectors, that together support signaling schemes for achieving approximately 23 information bits per detected photon. Implementing HPE schemes relies on accurate and stable pointing of narrow laser beams from space platforms using active control. Key developments needed for future technology infusion, following a successful DSOC technology demonstration, include, cost-effective ground infrastructure, long term reliability of space lasers and detection systems, and solutions for high precision laser ranging. The current status of the DSOC Project and plans for future development will be discussed in this paper.

Biswas, Abhijit↗
NASA NTRS1982

Improved Magnetic-Field-Component Resolvers

New resolvers for vectorially summing outputs of aircraft-mounted magnetometers are lighter and more economical to fabricate than conventional electromagnetic resolvers. One resolver is based on potentiometric principles, the second uses polarization filters, and the third has variable-capacitance elements. Optical, capacitive and potentiometric devices have applications in aircraft navigation systems.

Garner, H. D.↗
NASA NTRS2002

Clementine Observations of the Zodiacal Light and the Dust Content of the Inner Solar System

Using the Moon to occult the Sun, the Clementine spacecraft used its navigation cameras to map the inner zodiacal light at optical wavelengths over elongations of 3 approx. less than epsilon approx. less than 30 deg from the Sun. This surface brightness map is then used to infer the spatial distribution of interplanetary dust over heliocentric distances of about 10 solar radii to the orbit of Venus. The averaged ecliptic surface brightness of the zodiacal light falls off as Z(epsilon) is a member of epsilon(sup -2.45 +/- 0.05), which suggests that the dust cross-sectional density nominally falls off as sigma(r) is a member of r(sup - 1.45 +/- 0.05). The interplanetary dust also has an albedo of alpha approx. = 0.1 that is uncertain by a factor of approx. 2. Asymmetries of approx. 10% are seen in directions east-west and north-south of the Sun, and these may be due the giant planets' secular gravitational perturbations. We apply a simple model that attributes the zodiacal light as due to three dust populations having distinct inclination distributions, namely, dust from asteroids and Jupiter-family comets (JFCs) having characteristic inclinations of i approx. 7 deg, dust from Halley-type comets having i approx. 33 deg, and an isotropic cloud of dust from Oort Cloud comets. The best-fitting scenario indicates that asteroids + JFCs are the source of about 45% of the optical dust cross section seen in the ecliptic at 1 AU but that at least 89% of the dust cross section enclosed by a 1-AU-radius sphere is of a cometary origin. Each population's radial density variations can also deviate somewhat from the nominal sigma(r) is a member of r(sup -1.45). When these results are extrapolated out to the asteroid belt, we find an upper limit on the mass of the light-reflecting asteroidal dust that is equivalent to a 12-km asteroid, and a similar extrapolation of the isotropic dust cloud out to Oort Cloud distances yields a mass equivalent to a 30-km comet, although the latter mass is uncertain by orders of magnitude.

Hahn, Joseph M.↗
NASA NTRSDate not supplied

Optical Characterization of CLPS MiniatureLaser Retroreflector Arrays

Laser retroreflector arrays (LRAs) consisting of corner cube retroreflectors (CCRs) can act as fiducial markers for decades of laser ranging on the Moon and other planetary bodies. Upcoming lunar lander missions from government space agencies and commercial partners offer a unique opportunity to support lunar science and exploration through the deployment of small LRAs on lander decks. Placement of an LRA on the deck of a lander or rover enables tracking with an orbital laser altimeter to aprecision on the order of centimeters. When mounted alongside a suite of scientific instruments the LRA enables precise geolocation of those instruments in the lunar geodetic frame. Finally, optical markers such as LRAs can support precision autonomous navigation and landing regardless of lighting conditions, an especially valuable capability for lunar polar exploration where long shadows complicate terrain relative nagivation using imaging methods.

Daniel R. Cremons↗
NASA NTRSDate not supplied

Photonics for Space Flight Instruments

For the past 25 years, the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center’s Photonics Group in the Engineering Directorate has been substantially contributing to the flight design, development, production, testing and integration of many science and navigational instruments. The group has an extensive background in screening, qualifying, development and integration of commercial components for spaceflight applications. They have been willing to communicate lessons learned in packaging, part construction, materials selection, testing, and other facets of the design and production process critical to implementation for high-reliability systems. Summarized here is the last ten years of instrumentation development lessons learned and data collected from the subsystems down to the optoelectronic component level.

Spaceflight↗
NASA NTRSDate not supplied

NASA's Small Spacecraft and Distributed Systems: Development and Demonstration of Technologies Enabling Swarms and New Spacecraft Platforms with AI and Edge Computing

NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.

Jan Stupl↗
NASA NTRSDate not supplied

NASA's Small Spacecraft and Distributed Systems: Development and Demonstration of Technologies Enabling Swarms and New Spacecraft Platforms with AI and Edge Computing

NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.

Jan Stupl↗
NASA NTRSDate not supplied

Low SWaP Onboard Satellite Navigation, Guidance, and Control Technology

Onboard autonomy is a necessity for responsive space operations. Autonomous navigation, guidance, and control (NGC) enables space missions to reduce their dependence on high demand ground assets and costly ground personnel. It also allows for in-situ decision making and higher return on mission data. A flight software and hardware system providing this capability, called “autoNGC,” is currently being developed at NASA Goddard Space Flight Center for infusion into multiple future missions. The first build of autoNGC, providing autonomous navigation for lunar orbiting spacecraft, is targeted for completion by Fall 2024. It provides sensor fusion of multiple measurement types including pseudo-range from a weak signal Global Navigation Satellite Service (GNSS) receiver, 1-way and 2-way direct to Earth (DTE) range and Doppler, bearing and range from optical camera sensed images, and an accelerometer. AutoNGC is also being targeted for future missions that involve small body proximity operations, Sun Earth Libration point orbits, and distributed systems missions (DSMs) including those at outer planets. AutoNGC flight software is being built upon the plug-and-play architecture of the core Flight System (cFS) [Ref. 1]. Figure (Slide 7) shows the message-based software bus layout of various software applications (“apps”) consisting of the standard cFS apps and autoNGC interface apps and libraries. Accurate onboard navigation and timing is obtained through the Goddard Enhanced Onboard Navigation System (GEONS) software library [Ref. 2], which fuses different measurement types through an extended Kalman filter (EKF) framework. Optical measurements that are ingested in GEONS are provided by the cFS Goddard Image Analysis and Navigation Tool (cGIANT) app [Ref. 3]. This app processes optical images to extract the bearing angles of the centroid of the imaged body (near or far), the range to the imaged body, and/or of the features on the surface of a body to perform terrain relative navigation (TRN). Measurement of range to the body’s center of mass can also be derived from the detection of the limb. The first build of autoNGC for a lunar orbiting spacecraft is a minimal size, weight, and power (SWaP) hardware design allowing for inclusion into CubeSats and SmallSat-size class buses. Advancements in miniaturized space processors, such as the SpaceCube 3.0 Mini and the SpaceCube Mini-Z [Ref. 4] are utilized for low SWaP while maintaining a high level of performance. Figure (Slide 11) shows the composition of the first autoNGC build. The current enclosure design has dimensions 12 cm x 17 cm x 13.5 cm. The box mass is expected to be less than 2 kg, and the nominal power is 21 W. The hardware interfaces are designed for flexibility with a variety of sensor inputs. The achievable navigation performance depends on the sensors utilized, including the onboard clock for 1-way pseudo-range measurements. Analysis using a configuration that consists of weak signal GPS, TRN, and 1-way DTE has shown position and velocity accuracies of 10 meters and 2 cm/s (3-σ ) RSS, respectively, with onboard time knowledge estimated to better than 13 ns (3-σ ), for a spacecraft in a representative 12-hour eccentric lunar orbit. Other measurement types such as x-rays from known pulsars (called XNAV) and cross-links can also be processed in GEONS. With the plug-and-play architecture of autoNGC, cFS apps can easily be added and replaced, even after launch. Goddard is actively seeking partners to collaborate in the development of additional capabilities for autoNGC, including industry, academia, and others across the US Government. Plans are being formulated to make the autoNGC software platform available for use by any US government organization to leverage the non-recurring engineering associated with the development of onboard autonomous NGC 3 capabilities. As advancements in space qualified sensors, microprocessors, and algorithms are made, the autoNGC platform provides a ready starting point for inclusion of these technologies.

C. J. Gramling↗
NASA NTRS2011

Deep-Space Optical Communications: Visions, Trends, and Prospects

Current key initiatives in deep-space optical communications are treated in terms of historical context, contemporary trends, and prospects for the future. An architectural perspective focusing on high-level drivers, systems, and related operations concepts is provided. Detailed subsystem and component topics are not addressed. A brief overview of past ideas and architectural concepts sets the stage for current developments. Current requirements that might drive a transition from radio frequencies to optical communications are examined. These drivers include mission demand for data rates and/or data volumes; spectrum to accommodate such data rates; and desired power, mass, and cost benefits. As is typical, benefits come with associated challenges. For optical communications, these include atmospheric effects, link availability, pointing, and background light. The paper describes how NASA's Space Communication and Navigation Office will respond to the drivers, achieve the benefits, and mitigate the challenges, as documented in its Optical Communications Roadmap. Some nontraditional architectures and operations concepts are advanced in an effort to realize benefits and mitigate challenges as quickly as possible. Radio frequency communications is considered as both a competitor to and a partner with optical communications. The paper concludes with some suggestions for two affordable first steps that can yet evolve into capable architectures that will fulfill the vision inherent in optical communications.

space communication↗
NASA NTRS2000

Orbit Operations at 433 Eros: Navigation for the NEAR Shoemaker Mission

NASA's Near Earth Asteroid Rendezvous Mission began its record-setting exploration of the asteroid 433 Eros by inserting the spacecraft into orbit about Eros on February 14, 2000. This is the first spacecraft from any country to orbit an asteroid. The mission has overcome a failed insertion burn attempt on December 20, 1998, an event that would have ended most planetary missions, to return to the same target and successfully begin its science mapping a little more than a year later. Shortly after the successful insertion into orbit, the mission was renamed NEAR Shoemaker (NEAR) in memory of the late astronomer and geologist Eugene Shoemaker. NEAR will gather science data at Eros until February 14, 2001, which is the nominal end of mission. The NEAR mission is managed by the Johns Hopkins University, Applied Physics Laboratory in Laurel, Maryland. Since the initial mission concept in 1992, the design and implementation of the NEAR navigation system have been the responsibility of the Jet Propulsion Laboratory, California Institute of Technology. This presentation will show some of the unique features of navigation and mission design related to orbiting an asteroid and to designing a robust navigation system for the NEAR spacecraft. The problem of navigating a spacecraft about an asteroid is made difficult by the relative uncertainty in the asteroid physical properties which perturb the orbit: i.e., the mass, gravity field, and spin state. To help solve this problem, the navigation system for NEAR uses traditional DSN radio metric Doppler and range tracking, along with new technologies of optical landmark tracking and laser ranging to the asteroid surface. The experiences to date for each of these data types in the navigation solutions will be presented. Plans for the remainder of the NEAR mission will be presented, which include low orbits (down to 35 km radius circular orbits), and close flybys that may pass within 1 km of the surface. In addition, at the end of mission, NASA has approved a controlled descent and hovering phase that will culminate with the spacecraft impacting the surface. The maneuver planning for this final phase will also be presented.

Williams, B. G.↗
NASA NTRS2016

Enabling Communication and Navigation Technologies for Future Near Earth Science Missions

In 2015, the Earth Regimes Network Evolution Study (ERNESt) Team proposed a fundamentally new architectural concept, with enabling technologies, that defines an evolutionary pathway out to the 2040 timeframe in which an increasing user community comprised of more diverse space science and exploration missions can be supported. The architectural concept evolves the current instantiations of the Near Earth Network and Space Network through implementation of select technologies resulting in a global communication and navigation network that provides communication and navigation services to a wide range of space users in the Near Earth regime, defined as an Earth-centered sphere with radius of 2M Km. The enabling technologies include: High Rate Optical Communications, Optical Multiple Access (OMA), Delay Tolerant Networking (DTN), User Initiated Services (UIS), and advanced Position, Navigation, and Timing technology (PNT). This paper describes this new architecture, the key technologies that enable it and their current technology readiness levels. Examples of science missions that could be enabled by the technologies and the projected operational benefits of the architecture concept to missions are also described.

Networking↗
NASA NTRS1993

Scene segmentation of natural images using texture measures and back-propagation

Knowledge of the three-dimensional world is essential for many guidance and navigation applications. A sequence of images from an electro-optical sensor can be processed using optical flow algorithms to provide a sparse set of ranges as a function of azimuth and elevation. A natural way to enhance the range map is by interpolation. However, this should be undertaken with care since interpolation assumes continuity of range. The range is continuous in certain parts of the image and can jump at object boundaries. In such situations, the ability to detect homogeneous object regions by scene segmentation can be used to determine regions in the range map that can be enhanced by interpolation. The use of scalar features derived from the spatial gray-level dependence matrix for texture segmentation is explored. Thresholding of histograms of scalar texture features is done for several images to select scalar features which result in a meaningful segmentation of the images. Next, the selected scalar features are used with a neural net to automate the segmentation procedure. Back-propagation is used to train the feed forward neural network. The generalization of the network approach to subsequent images in the sequence is examined. It is shown that the use of multiple scalar features as input to the neural network result in a superior segmentation when compared with a single scalar feature. It is also shown that the scalar features, which are not useful individually, result in a good segmentation when used together. The methodology is applied to both indoor and outdoor images.

Sridhar, Banavar↗