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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Optical processing for range and attitude determination

A rugged, miniaturized, optical cross-correlator that recognizes a single object is particularly suitable for performing a single-vision function, such as pattern recognition for semi-autonomous navigation, landing, and docking of vehicles to a pre-designated landing mark. The optical cross-correlator, with a video input from a simple imaging system and the output of the optical correlation plane processed using the standard star tracker software, produces sufficient information for a spacecraft's terminal homing navigation system to complete a docking maneuver.

Scholl, M. S.↗
NASA NTRS1975

The Deep Space Network

This report presents DSN progress in flight project support, tracking and data acquisition (TDA) research and technology, network engineering, hardware and software implementation, and operations. Each issue presents material in some, but not all, of the following categories in the order indicated. - Description of the DSN - Mission Support Ongoing Planetary/Interplanetary Flight Projects Advanced Flight Projects - Radio Science - Special Projects - Supporting Research and Technology Tracking and Ground-Based Navigation Communications--Spacecraft/Ground Station Control and Operations Technology Network Control and Data Processing - Network and Facility Engineering and Implementation Network Network Operations Control Center Ground Communications Deep Space Stations - Operations Network Operations Network Operations Control Center Ground Communications Deep Space Stations - Program Planning TDA Planning Quality Assurance In each issue, the part entitled "Description of the DSN" describes the functions and facilities of the DSN and may report the current configuration of one of the five DSN systems (Tracking, Telemetry, Command, Monitor & Control, and Test & Training). The work described in this report series is either performed or managed by the Tracking and Data Acquisition organization of JPL for NASA.

Tracking and Data Acquisition organization↗
NASA NTRS1982

Modeling methodology for MLS range navigation system errors using flight test data

Flight test data was used to develop a methodology for modeling MLS range navigation system errors. The data used corresponded to the constant velocity and glideslope approach segment of a helicopter landing trajectory. The MLS range measurement was assumed to consist of low frequency and random high frequency components. The random high frequency component was extracted from the MLS range measurements. This was done by appropriate filtering of the range residual generated from a linearization of the range profile for the final approach segment. This range navigation system error was then modeled as an autoregressive moving average (ARMA) process. Maximum likelihood techniques were used to identify the parameters of the ARMA process.

Karmali, M. S.↗
NASA NTRS1983

The Telecommunications and Data Aquisition Report

Tracking and ground-based navigation techniques are discussed in relation to DSN advanced systems. Network data processing and productivity are studied to improve management planning methods. Project activities for upgrading DSN facilities are presented.

Posner, E. C.↗
NASA NTRS1992

Onboard System Processes SAR Data

Aircraft Flight Correlator (AFC) computing system, mounted with AIRSAR synthetic-aperture-radar (SAR) system, supplements recording and postflight analysis, processing portion of data in real or nearly real time to provide imagery for rapid evaluation. Facilitates diagnosis of SAR equipment or adjustment of parameters of experiment. Operates in two modes: "quick-look" mode, data processed in 10 minutes into high-resolution image; and "real-time" mode, data processed in real time to reduced resolution. Also used as aid to navigation.

Carande, Richard E.↗
NASA NTRS1991

Office of Space Flight standard spaceborne Global Positioning System user equipment project

The Global Positioning System (GPS) provides users autonomous, real-time navigation capability. A vehicle equipped with GPS user equipment can receive and process signals transmitted by a constellation of GPS satellites and derive from the resulting measurements the vehicle's position and velocity. Specified accuracies range from 16 to 76 meters and 0.1 to 1.0 meters/second for position and velocity, respectively. In a rendezvous and docking scenario, the use of a technique called relative GPS can provide range and range rate accuracies on the order of 1 meter and 0.01 meters/second, respectively. Relative GPS requires both vehicles to be equipped with GPS user equipment and a data communication link for transmission of GPS data and GPS satellite selection coordination information. Through coordinated satellite selection, GPS measurement errors common to both users are cancelled and improved relative position and velocity accuracies are achieved. The background, the design approach, the expected performance and capabilities, the development plan, and the project status are described. In addition, a description of relative GPS, the possible GPS hardware and software configurations, and its application to automated rendezvous and capture are presented.

Saunders, Penny E.↗
NASA NTRS1994

McIDAS-eXplorer: A version of McIDAS for planetary applications

McIDAS-eXplorer is a set of software tools developed for analysis of planetary data published by the Planetary Data System on CD-ROM's. It is built upon McIDAS-X, an environment which has been in use nearly two decades now for earth weather satellite data applications in research and routine operations. The environment allows convenient access, navigation, analysis, display, and animation of planetary data by utilizing the full calibration data accompanying the planetary data. Support currently exists for Voyager images of the giant planets and their satellites; Magellan radar images (F-MIDR and C-MIDR's, global map products (GxDR's), and altimetry data (ARCDR's)); Galileo SSI images of the earth, moon, and Venus; Viking Mars images and MDIM's as well as most earth based telescopic images of solar system objects (FITS). The NAIF/JPL SPICE kernels are used for image navigation when available. For data without the SPICE kernels (such as the bulk of the Voyager Jupiter and Saturn imagery and Pioneer Orbiter images of Venus), tools based on NAIF toolkit allow the user to navigate the images interactively. Multiple navigation types can be attached to a given image (e.g., for ring navigation and planet navigation in the same image). Tools are available to perform common image processing tasks such as digital filtering, cartographic mapping, map overlays, and data extraction. It is also possible to have different planetary radii for an object such as Venus which requires a different radius for the surface and for the cloud level. A graphical user interface based on Tel-Tk scripting language is provided (UNIX only at present) for using the environment and also to provide on-line help. It is possible for end users to add applications of their own to the environment at any time.

Limaye, Sanjay S.↗
NASA NTRS2002

2001 Mars Odyssey Project report

The Mars Odyssey orbiter was launched on April 7, 2001, and arrived at Mars on October 24, 2001. The orbiter carries scientific instruments that will determine surface elemental composition, mineralogy and morphology, and measure the Mars radiation environment from orbit. In addition, the orbiter will serve as a data relay for future surface missions. This paper will present an overview of the Odyssey project, including the key elements of the spacecraft design, mission design and navigation, mission operations, and the science approach. The project's risk management process will be described. Initial findings of the science team will be summarized.

Mars Odyssey↗
NASA NTRS2008

NASA Tech Briefs, December 2008

Topics covered include: Crew Activity Analyzer; Distributing Data to Hand-Held Devices in a Wireless Network; Reducing Surface Clutter in Cloud Profiling Radar Data; MODIS Atmospheric Data Handler; Multibeam Altimeter Navigation Update Using Faceted Shape Model; Spaceborne Hybrid-FPGA System for Processing FTIR Data; FPGA Coprocessor for Accelerated Classification of Images; SiC JFET Transistor Circuit Model for Extreme Temperature Range; TDR Using Autocorrelation and Varying-Duration Pulses; Update on Development of SiC Multi-Chip Power Modules; Radio Ranging System for Guidance of Approaching Spacecraft; Electromagnetically Clean Solar Arrays; Improved Short-Circuit Protection for Power Cells in Series; Electromagnetically Clean Solar Arrays; Logic Gates Made of N-Channel JFETs and Epitaxial Resistors; Improved Short-Circuit Protection for Power Cells in Series; Communication Limits Due to Photon-Detector Jitter; System for Removing Pollutants from Incinerator Exhaust; Sealing and External Sterilization of a Sample Container; Converting EOS Data from HDF-EOS to netCDF; HDF-EOS 2 and HDF-EOS 5 Compatibility Library; HDF-EOS Web Server; HDF-EOS 5 Validator; XML DTD and Schemas for HDF-EOS; Converting from XML to HDF-EOS; Simulating Attitudes and Trajectories of Multiple Spacecraft; Specialized Color Function for Display of Signed Data; Delivering Alert Messages to Members of a Work Force; Delivering Images for Mars Rover Science Planning; Oxide Fiber Cathode Materials for Rechargeable Lithium Cells; Electrocatalytic Reduction of Carbon Dioxide to Methane; Heterogeneous Superconducting Low-Noise Sensing Coils; Progress toward Making Epoxy/Carbon-Nanotube Composites; Predicting Properties of Unidirectional-Nanofiber Composites; Deployable Crew Quarters; Nonventing, Regenerable, Lightweight Heat Absorber; Miniature High-Force, Long-Stroke SMA Linear Actuators; "Bootstrap" Configuration for Multistage Pulse-Tube Coolers; Reducing Liquid Loss during Ullage Venting in Microgravity; Ka-Band Transponder for Deep-Space Radio Science; Replication of Space-Shuttle Computers in FPGAs and ASICs; Demisable Reaction-Wheel Assembly; Spatial and Temporal Low-Dimensional Models for Fluid Flow; Advanced Land Imager Assessment System; Range Imaging without Moving Parts.

Source record↗
NASA NTRS2024

Climate Extremes and Risks: Links Between Climate Science and Decision-Making

The World Climate Research Programme (WCRP) envisions a future where actionable climate information is universally accessible, supporting decision makers in preparing for and responding to climate change. In this perspective, we advocate for enhancing links between climate science and decision-making through a better and more decision-relevant understanding of climate impacts. The proposed framework comprises three pillars: climate science, impact science, and decision-making, focusing on generating seamless climate information from sub-seasonal, seasonal, decadal to century timescales informed by observed climate events and their impacts. The link between climate science and decision-making has strengthened in recent years, partly owing to undeniable impacts arising from disastrous weather extremes. Enhancing decision-relevant understanding involves utilizing lessons from past extreme events and implementing impact-based early warning systems to improve resilience. Integrated risk assessment and management require a comprehensive approach that encompasses good knowledge about possible impacts, hazard identification, monitoring, and communication of risks while acknowledging uncertainties inherent in climate predictions and projections, but not letting the uncertainty lead to decision paralysis. The importance of data accessibility, especially in the Global South, underscores the need for better coordination and resource allocation. Strategic frameworks should aim to enhance impact-related and open-access climate services around the world. Continuous improvements in predictive modeling and observational data are critical, as is ensuring that climate science remains relevant to decision makers locally and globally. Ultimately, fostering stronger collaborations and dedicated investments to process and tailor climate data will enhance societal preparedness, enabling communities to navigate the complexities of a changing climate effectively.

climate extremes↗
NASA NTRS2019

Rapid Development of the Seeker Free-Flying Inspector Guidance, Navigation, and Control System

Seeker is an automated extravehicular free-flying inspector CubeSat designed and built in-house at the Johnson Space Center (JSC). As a Class 1E project funded by the International Space Station (ISS) Program, Seeker had a streamlined process to flight certification, but the vehicle had to be designed, developed, tested, and delivered within approximately one year after authority to pro-ceed (ATP) and within a $1.8 million budget. These constraints necessitated an expedited Guidance, Navigation, and Control (GNC) development schedule, development began with a navigation sensor trade study using Linear Covariance (LinCov) analysis and a rapid sensor downselection process, resulting in the use of commercial off-the-shelf (COTS) sensors which could be procured quickly and subjected to in-house environmental testing to qualify them for flight. A neural network was used to enable a COTS camera to provide bearing measurements for visual navigation. The GNC flight software (FSW) algorithms utilized lean development practices and leveraged the Core Flight Software (CFS) architecture to rapidly develop the GNC system, tune the system parameters, and verify performance in simulation. This pace was anchored by several Hardware-Software Integration (HSI) milestones, which forced the Seeker GNC team to develop the interfaces both between hardware and software and between the GNC domains early in the project and to enable a timely delivery.

Sullivan, Jacob↗
NASA NTRSDate not supplied

Building Lunar Maps for Terrain Relative Navigation and Hazard Detection Applications

Terrain Relative Navigation (TRN) systems localize a spacecraft with respect to a map of the surface by comparing descent imagery to that reference map. The spacecraft position estimates can only be as accurate as the reference map itself. Accurate map products that are based on orbital reconnaissance data must be validated for navigation applications to ensure that all relevant error sources are minimized. Currently available map products have been generated for scientific applications, so the need for accurate TRN maps remains a gap to be filled for upcoming lunar lander missions, in particular missions to the South Pole region. Additionally, representative high-resolution maps that contain lander-scale features are needed for successful development and testing of Hazard Detection (HD) systems. This paper describes one of NASA’s current efforts to develop benchmark data sets that can be used for developing and testing TRN and HD algorithms as well as suggested processes and metrics for generating and validating lunar maps that can be used for navigation and hazard detection.

Lunar Maps↗
NASA NTRS2022

Building Lunar Maps for Terrain Relative Navigation and Hazard Detection Applications

Terrain Relative Navigation (TRN) systems that localize a spacecraft with respect to a map of the surface by comparing descent imagery to that reference map can only be as accurate as the reference map itself. Accurate map products that are based on orbital reconnaissance data must be validated for navigation applications to ensure that all relevant error sources are minimized. Currently available map products have been generated for scientific applications, so the need for accurate TRN maps remains a gap to be filled for upcoming lunar lander missions, in particular missions to the South Pole region. Additionally, representative high-resolution maps that contain lander-scale features are needed for successful development and testing of Hazard Detection (HD) systems. This paper describes one of NASA’s current efforts to develop benchmark data sets that can be used for developing and testing TRN and HD algorithms as well as suggested processes and metrics for generating and validating lunar maps that can be used for navigation and hazard detection.

Beyer, Ross A.↗
NASA NTRSDate not supplied

Guidance, Navigation, and Control for Laser-Based Non-Cooperative Target Detumbling

Orbital debris is a well known and growing problem presenting risks to the future of spaceflight. Many pieces of debris are defunct satellites or rocket upper stages. These large objects could generate an exponentially growing cloud of debris should they be involved in a collision, i.e., Kessler Syndrome. Future orbital debris remediation efforts often propose perturbing the orbit of these large targets to mitigate risk. These plans often involve non-cooperative rendezvous. In the absence of active control, the targets are expected to be tumbling which makes rendezvous a dangerous prospect. In this work we describe a guidance, navigation, and control system for a contactless non-cooperative target detumbling methodology which will significantly increase the safety of non-cooperative rendezvous. An onboard laser generates thrust on the target by ablating its surface material. This thrust is used to control target attitude. Our guidance, navigation, and control system is able to estimate relative pose, target the laser, and maintain formation flight during the detumbling process. The system is validated with Monte Carlo simulation in a variety of scenarios.

Guidance↗
NASA NTRS2019

Rapid Development of the Seeker Free-Flying Inspector Guidance, Navigation, and Control System

Seeker is an automated extravehicular free-flying inspector CubeSat designed and built in-house at the Johnson Space Center (JSC). As a Class 1E project funded by the International Space Station (ISS) Program, Seeker had a stream-lined process to flight certification, but the vehicle had to be designed, developed, tested, and delivered within approximately one year after authority to proceed (ATP) and within a $1.8 million budget. These constraints necessitated an expedited Guidance, Navigation, and Control (GNC) development schedule. Development began with a navigation sensor trade study using Linear Covariance (LinCov) analysis and a rapid sensor down-selection process, resulting in the use of commercial off-the-shelf (COTS) sensors which could be procured quickly and subjected to in-house environmental testing to qualify them for flight. A neural network was used to enable a COTS camera to provide bearing measure-ments for visual navigation. The GNC flight software (FSW) algorithms utilized lean development practices and leveraged the Core Flight Software (CFS) architecture to rapidly develop the GNC system, tune the system parameters, and verify performance in simulation. This pace was anchored by several Hardware-Software Integration (HSI) milestones, which forced the Seeker GNC team to develop the interfaces both between hardware and software and between the GNC domains early in the project and to enable a timely delivery.

Sullivan, Jake↗
NASA NTRS1994

A reactive system for open terrain navigation: Performance and limitations

We describe a core system for autonomous navigation in outdoor natural terrain. The system consists of three parts: a perception module which processes range images to identify untraversable regions of the terrain, a local map management module which maintains a representation of the environment in the vicinity of the vehicle, and a planning module which issues commands to the vehicle controller. Our approach is to use the concept of 'early traversability evaluation', and on the use of reactive planning for generating commands to drive the vehicle. We argue that our approach leads to a robust and efficient navigation system. We illustrate our approach by an experiment in which a vehicle travelled autonomously for one kilometer through unmapped cross-country terrain.

Langer, D.↗
NASA NTRS2007

Estimation of Cometary Rotation Parameters Based on Camera Images

The purpose of the Rosetta mission is the in situ analysis of a cometary nucleus using both remote sensing equipment and scientific instruments delivered to the comet surface by a lander and transmitting measurement data to the comet-orbiting probe. Following a tour of planets including one Mars swing-by and three Earth swing-bys, the Rosetta probe is scheduled to rendezvous with comet 67P/Churyumov-Gerasimenko in May 2014. The mission poses various flight dynamics challenges, both in terms of parameter estimation and maneuver planning. Along with spacecraft parameters, the comet's position, velocity, attitude, angular velocity, inertia tensor and gravitatonal field need to be estimated. The measurements on which the estimation process is based are ground-based measurements (range and Doppler) yielding information on the heliocentric spacecraft state and images taken by an on-board camera yielding informaton on the comet state relative to the spacecraft. The image-based navigation depends on te identification of cometary landmarks (whose body coordinates also need to be estimated in the process). The paper will describe the estimation process involved, focusing on the phase when, after orbit insertion, the task arises to estimate the cometary rotational motion from camera images on which individual landmarks begin to become identifiable.

Spindler, Karlheinz↗
NASA NTRS1990

Using connected-element interferometer phase-delay data for Magellan navigation in Venus orbit

The pointing accuracy needed to support Magellan's Synthetic Aperture Radar mapping of Venus places stringent requirements on navigation accuracy. This need is met with a combination of two-way Doppler and narrowband delta Very Long Baseline Interferometer (delta VLBI) data, which are capable of determining the spacecraft's orbit to the required level, typically about one-kilometer position uncertainty. Differenced Doppler (two-way Doppler minus three-way Doppler) is also capable of meeting mission navigation requirements, and serves as a backup to narrowband delta VLBI. The Magellan Project specifies that the turn-around time for processing narrowband delta VLBI data must be 12 hours or less, a very difficult requirement to meet operationally. The use of phase-delay data, taken from a Connected-Element Interferometer (CEI) with a 21-km baseline, for Magellan orbit determination was investigated to determine if navigation performance comparable with narrowband delta VLBI and differenced Doppler could be achieved. CEI possesses an operational advantage over delta VLBI data in that the observables are constructed in near-real time, thus greatly reducing the turn-around time needed to process the data, relative to the off-line system used to generate delta VLBI observables. Unfortunately, the results indicate that CEI data are much less powerful than narrowband delta VLBI and differenced Doppler for orbiter navigation, although there was some marginal improvement over the navigation performance obtained when only two-way Doppler data were used.

Thurman, S. W.↗