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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 163 records · Page 9
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NASA NTRS2000

Preliminary Operational Results of the TDRSS Onboard Navigation System (TONS) for the Terra Mission

The Earth Observing System Terra spacecraft was launched on December 18, 1999, to provide data for the characterization of the terrestrial and oceanic surfaces, clouds, radiation, aerosols, and radiative balance. The Tracking and Data Relay Satellite System (TDRSS) Onboard Navigation System (ONS) (TONS) flying on Terra provides the spacecraft with an operational real-time navigation solution. TONS is a passive system that makes judicious use of Terra's communication and computer subsystems. An objective of the ONS developed by NASA's Goddard Space Flight Center (GSFC) Guidance, Navigation and Control Center is to provide autonomous navigation with minimal power, weight, and volume impact on the user spacecraft. TONS relies on extracting tracking measurements onboard from a TDRSS forward-link communication signal and processing these measurements in an onboard extended Kalman filter to estimate Terra's current state. Terra is the first NASA low Earth orbiting mission to fly autonomous navigation which produces accurate results. The science orbital accuracy requirements for Terra are 150 meters (m) (3sigma) per axis with a goal of 5m (1 sigma) RSS which TONS is expected to meet. The TONS solutions are telemetered in real-time to the mission scientists along with their science data for immediate processing. Once set in the operational mode, TONS eliminates the need for ground orbit determination and allows for a smooth flow from the spacecraft telemetry to planning products for the mission team. This paper will present the preliminary results of the operational TONS solution available from Terra.

Gramling, Cheryl↗
NASA NTRS2001

Classification Experiments on Real-World Texture

Many papers have been published concerning the analysis of visual texture and yet, very few application domains use texture for image classification. A possible reason for this low transfer of the technology is the lack of experience and testing in real-world imagery. In this paper, we assess the performance of texture-based classification methods on a number of real-world images relevant to autonomous navigation on cross-country terrain and to autonomous geology. Texture analysis will form part of the closed loop that allows a robotic system to navigate autonomously. We have implemented two different classifiers on features extracted by Gabor filter banks. The first classifier models feature distributions for each texture class using a mixture of Gaussians. Classification is performed using Maximum Likelihood. The second classifier represents local statistics using marginal histograms of the features over a region centered on the pixel to be classified. We measure system performance by comparison to ground truth image labels.

image segmentation↗
NASA NTRS2009

Autonomous Optical Lunar Navigation

The performance of optical autonomous navigation is investigated for low lunar orbits and for high elliptical lunar orbits. Various options for employing the camera measurements are presented and compared. Strategies for improving navigation performance are developed and applied to the Orion vehicle lunar mission

Zanetti, Renato↗
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 NTRS2016

Visual Odometry for Autonomous Deep-Space Navigation Project

Autonomous rendezvous and docking (AR&D) is a critical need for manned spaceflight, especially in deep space where communication delays essentially leave crews on their own for critical operations like docking. Previously developed AR&D sensors have been large, heavy, power-hungry, and may still require further development (e.g. Flash LiDAR). Other approaches to vision-based navigation are not computationally efficient enough to operate quickly on slower, flight-like computers. The key technical challenge for visual odometry is to adapt it from the current terrestrial applications it was designed for to function in the harsh lighting conditions of space. This effort leveraged Draper Laboratory’s considerable prior development and expertise, benefitting both parties. The algorithm Draper has created is unique from other pose estimation efforts as it has a comparatively small computational footprint (suitable for use onboard a spacecraft, unlike alternatives) and potentially offers accuracy and precision needed for docking. This presents a solution to the AR&D problem that only requires a camera, which is much smaller, lighter, and requires far less power than competing AR&D sensors. We have demonstrated the algorithm’s performance and ability to process ‘flight-like’ imagery formats with a ‘flight-like’ trajectory, positioning ourselves to easily process flight data from the upcoming ‘ISS Selfie’ activity and then compare the algorithm’s quantified performance to the simulated imagery. This will bring visual odometry beyond TRL 5, proving its readiness to be demonstrated as part of an integrated system.Once beyond TRL 5, visual odometry will be poised to be demonstrated as part of a system in an in-space demo where relative pose is critical, like Orion AR&D, ISS robotic operations, asteroid proximity operations, and more.

Robinson, Shane↗
NASA NTRS2016

Visual Odometry for Autonomous Deep-Space Navigation Project

Autonomous rendezvous and docking (AR&D) is a critical need for manned spaceflight, especially in deep space where communication delays essentially leave crews on their own for critical operations like docking. Previously developed AR&D sensors have been large, heavy, power-hungry, and may still require further development (e.g. Flash LiDAR). Other approaches to vision-based navigation are not computationally efficient enough to operate quickly on slower, flight-like computers. The key technical challenge for visual odometry is to adapt it from the current terrestrial applications it was designed for to function in the harsh lighting conditions of space. This effort leveraged Draper Laboratory's considerable prior development and expertise, benefitting both parties. The algorithm Draper has created is unique from other pose estimation efforts as it has a comparatively small computational footprint (suitable for use onboard a spacecraft, unlike alternatives) and potentially offers accuracy and precision needed for docking. This presents a solution to the AR&D problem that only requires a camera, which is much smaller, lighter, and requires far less power than competing AR&D sensors. We have demonstrated the algorithm's performance and ability to process 'flight-like' imagery formats with a 'flight-like' trajectory, positioning ourselves to easily process flight data from the upcoming 'ISS Selfie' activity and then compare the algorithm's quantified performance to the simulated imagery. This will bring visual odometry beyond TRL 5, proving its readiness to be demonstrated as part of an integrated system. Once beyond TRL 5, visual odometry will be poised to be demonstrated as part of a system in an in-space demo where relative pose is critical, like Orion AR&D, ISS robotic operations, asteroid proximity operations, and more.

Robinson, Shane↗
NASA NTRS1996

Autonomous Optical Navigation for Interplanetary Missions

The automation of interplanetary spacecraft is becoming increasingly desirable to meet various mission requirements. A prototype of an autonomous spacecraft which will fly by an asteroid and comet is slated for flight in mid-1998 as part of NASA's New Millenium Program.

optical↗
NASA NTRS2017

Autonomous Guidance Navigation and Control for Agile Quadrotors Using Polynomial Trajectory Planning and L1 Adaptive Control

We address the challenge to allow efficient autonomous flight in real world environments, both indoor and outdoor. We use a straight-line SE-SCP (Spherical Expansion and Sequential Convex Programming) [algorithm] to find an initial route through the environment and minimum snap trajectory generation using piecewise polynomials. Then, we implement an adaptive robust control able to address some robustness issues for quadrotors in outdoor flight, such as mass variation and wind disturbances. Coupling these techniques we allow high-speed and aggressive autonomous flight through obstacle-dense indoor environments, as well as address outdoor disturbances.

Landolfi, Mattia↗
NASA NTRS2019

Lunar Navigation Beacon Network Using Global Navigation Satellite System Receivers

With the increasing traffic in the lunar regime as part of NASA efforts to return humans to the moon. In order to support these missions, new capabilities are needed to support autonomous navigation and inter-asset communication. Additionally, with maturation and flight demonstration of increasingly capable small satellites, there is an opportunity to embed technology into a small spacecraft as part of companion missions. This paper addresses one such architecture, taking advantage of a lunar lander vehicle to host a companion spacecraft to build out lunar navigation and communication capability. The backbone of this spacecraft is the Navigator GPS receiver. This hardware has continually broken records on high altitude GPS coverage and has the potential to support autonomous navigation at lunar distances. This research proposes a large cubesat built around this technology and catching a ride to the moon via a lander mission. The concept of operations includes the spacecraft deploying prior to the lunar sphere of influence and maneuvering to enter into a lunar orbit. With the Navigator receiver, this spacecraft is capable of a large amount of autonomy, with a limited need for ground-based orbit determination. This spacecraft will fly alongside the lander, acting as a navigation reference during cruise, descent, and post-landing for mission validation. To assess this mission scenario, three aspects are covered in detail herein: the feasibility and mission requirements for entering into a lunar orbit given deployment along a lander surface-bound trajectory, the performance capability of the receiver along this transfer trajectory and in lunar orbit, and the ability to support navigation of the lander itself. These three areas are discussed in detail, providing results that support feasibility of the mission and determination of initial requirements.

Anzalone, Evan J.↗
NASA NTRS1988

Search Problems in Mission Planning and Navigation of Autonomous Aircraft

An architecture for the control of an autonomous aircraft is presented. The architecture is a hierarchical system representing an anthropomorphic breakdown of the control problem into planner, navigator, and pilot systems. The planner system determines high level global plans from overall mission objectives. This abstract mission planning is investigated by focusing on the Traveling Salesman Problem with variations on local and global constraints. Tree search techniques are applied including the breadth first, depth first, and best first algorithms. The minimum-column and row entries for the Traveling Salesman Problem cost matrix provides a powerful heuristic to guide these search techniques. Mission planning subgoals are directed from the planner to the navigator for planning routes in mountainous terrain with threats. Terrain/threat information is abstracted into a graph of possible paths for which graph searches are performed. It is shown that paths can be well represented by a search graph based on the Voronoi diagram of points representing the vertices of mountain boundaries. A comparison of Dijkstra's dynamic programming algorithm and the A* graph search algorithm from artificial intelligence/operations research is performed for several navigation path planning examples. These examples illustrate paths that minimize a combination of distance and exposure to threats. Finally, the pilot system synthesizes the flight trajectory by creating the control commands to fly the aircraft.

Krozel, James A.↗
NASA NTRS1997

Autonomous Mobility, Navigation, and Control for Venus Aerobots

Ballons systems which operate under robotic contol, called aerobots, offer rich potential for exploration of the planets. Telerobotics technology allows an aerobot to control its vertical motion and exploit prevailing winds to autonomously move to different planetery locations.

Control for Venus Aerobots Robotic Control Navigat↗
NASA NTRS2019

Predicted Performance of an X-Ray Navigation System for Future Deep Space and Lunar Missions

In November 2017, the NASA Goddard Space Flight Center (GSFC) Station Explorer for X-ray Timing and Navigation Technology (SEXTANT) experiment successfully demonstrated the feasibility of X-ray Pulsar Navigation (XNAV) as part of the Neutron Star Interior Composition Explorer (NICER) mission, which is an X-ray Astrophysics Mission of Opportunity currently operating onboard the International Space Station (ISS). XNAV provides a GPS-like absolute autonomous navigation and timing capability available anywhere in the Solar System and beyond. While the most significant benefits of XNAV are expected to come in support of very deep-space missions, the absolute autonomous navigation and timing capability also has utility for inner Solar System missions where increased autonomy or backup navigation and timing services are required, e.g., address loss of communication scenarios.The NASA commitment to develop a Gateway to support exploration of the Moon and eventually Mars, as well as current and future robotic missions such as James Webb Space Telescope (JWST), New Horizons, and much more, certainly will tax the existing ground based infrastructure in terms of availability. There- fore, an extended look at the feasibility and potential performance of XNAV for comparable missions is warranted. In this paper, we briefly review the XNAV concept and present case studies of its utility and performance for a Gateway orbit, Sun-Earth libration orbit, and a deep space transit trajectory.

Getchius, Joel↗
NASA NTRS1991

Autonomous reconfigurable GPS/INS navigation and pointing system for rendezvous and docking

This paper describes the results of an integrated navigation and pointing system software development effort sponsored by the NASA MSFC through a SBIR Phase 2 Program. The integrated Global Positioning System (GPS)/Inertial Navigation System (INS) implements an autonomous navigation filter that is reconfigurable in real-time to accommodate mission contingencies. An onboard expert system monitors the spacecraft status and reconfigures the navigation filter accordingly, to optimize the system performance. The navigation filter is a multi-mode Kalman filter to estimate the spacecraft position, velocity, and attitude. Three different GPS-based attitude determination techniques, namely, velocity vector matching, attitude vector matching, and interferometric processing, are implemented to encompass different mission contingencies. The integrated GPS/INS navigation filter will use any of these techniques depending on the mission phase and the state of the sensors. The first technique, velocity vector matching, uses the GPS velocity measurement to estimate the INS velocity errors and exploits the correlation between INS velocity and attitude errors to estimate the attitude. The second technique, attitude vector matching, uses INS gyro measurements and GPS carrier phase (integrated Doppler) measurements during a spacecraft rotation maneuver to determine the attitude. Both of these techniques require only one GPS antenna onboard to determine the spacecraft attitude. The third technique, interferometric processing, requires use of multiple GPS antennae. In order to determine 3-axis body attitude, three GPS antennae (2 no-coplanor baselines) are required.

Upadhyay, Triveni N.↗
NASA NTRS2016

Navigation Architecture for a Space Mobile Network

The Tracking and Data Relay Satellite System (TDRSS) Augmentation Service for Satellites (TASS) is a proposed beacon service to provide a global, space based GPS augmentation service based on the NASA Global Differential GPS (GDGPS) System. The TASS signal will be tied to the GPS time system and usable as an additional ranging and Doppler radiometric source. Additionally, it will provide data vital to autonomous navigation in the near Earth regime, including space weather information, TDRS ephemerides, Earth Orientation Parameters (EOP), and forward commanding capability. TASS benefits include enhancing situational awareness, enabling increased autonomy, and providing near real-time command access for user platforms. As NASA Headquarters' Space Communication and Navigation Office (SCaN) begins to move away from a centralized network architecture and towards a Space Mobile Network (SMN) that allows for user initiated services, autonomous navigation will be a key part of such a system. This paper explores how a TASS beacon service enables the Space Mobile Networking paradigm, what a typical user platform would require, and provides an in-depth analysis of several navigation scenarios and operations concepts. This paper provides an overview of the TASS beacon and its role within the SMN and user community. Supporting navigation analysis is presented for two user mission scenarios: an Earth observing spacecraft in low earth orbit (LEO), and a highly elliptical spacecraft in a lunar resonance orbit. These diverse flight scenarios indicate the breadth of applicability of the TASS beacon for upcoming users within the current network architecture and in the SMN.

Data Relay↗
NASA NTRS2016

Navigation Architecture For A Space Mobile Network

The Tracking and Data Relay Satellite System (TDRSS) Augmentation Service for Satellites (TASS) is a proposed beacon service to provide a global, space-based GPS augmentation service based on the NASA Global Differential GPS (GDGPS) System. The TASS signal will be tied to the GPS time system and usable as an additional ranging and Doppler radiometric source. Additionally, it will provide data vital to autonomous navigation in the near Earth regime, including space weather information, TDRS ephemerides, Earth Orientation Parameters (EOP), and forward commanding capability. TASS benefits include enhancing situational awareness, enabling increased autonomy, and providing near real-time command access for user platforms. As NASA Headquarters Space Communication and Navigation Office (SCaN) begins to move away from a centralized network architecture and towards a Space Mobile Network (SMN) that allows for user initiated services, autonomous navigation will be a key part of such a system. This paper explores how a TASS beacon service enables the Space Mobile Networking paradigm, what a typical user platform would require, and provides an in-depth analysis of several navigation scenarios and operations concepts.

Satellite↗
NASA NTRS2006

Deep impact attitude estimator design and flight performance

In July, 2005 Deep Impact successfully impacted comet Tempel-1 and imaged the crater evolution. To achieve this, an onboard autonomous navigation system had to estimate the trajectory and maneuver the Impactor spacecraft into the comet's path. A similar system, operating on the Flyby spacecraft, calculated the impact location for imaging. At the heart of each autonomous navigation system is the attitude and gyro bias estimator using star trackers and gyros. The encounter geometry and timing placed stringent demands on attitude bias magnitude and drift calling for sequenced tuning of the respective filters. This paper describes the attitude and gyro bias estimator algorithms, the estimator flight performance and particular challenges overcome by the team leading up to a spectacular encounter.

Tempel-1↗