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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Navigation accuracy at Jupiter and Saturn using optical observations of planetary satellites

Autonomous on-board navigation has the potential to enable new types of missions and decrease reliance on NASA’s Deep Space Network for navigation purposes. Previous results have shown that navigating with only optical images of asteroids is feasible for inner planet cruise. In this study, we show that images of natural satellites can be used to navigate during approach and tour phases around the gas giants. We investigate the Jupiter and Saturn systems here, and specifically assess the performance of optical-only navigation for the Juno, Europa Clipper, and Cassini trajectories. Early approach phases and tours at Jupiter would require radiometric data to navigate, but the performance of optical-only data rivals the as-flown performance for Cassini at Saturn.

Broschart, Stephen B.↗
NASA NTRS1990

High-accuracy Mars approach navigation with radio metric and optical data

The aerocapture of a space vehicle on hyperbolic approach to Mars results in tight navigation requirements at atmospheric entry. The purpose of this paper is to examine several different methods for approach navigation and to determine what accuracies are possible. The methods are broken into four groups as follows (1) navigation with only Deep Space Network (DSN) tracking of the approach vehicle, (2) navigation with the DSN plus ranging between the approach vehicle and spacecraft in orbit about Mars, (3) navigation with the DSN plus optical data involving the Martian moons, and (4) navigation with DSN range data and differenced range data involving the approach spacecraft and orbiters at Mars. If the current modeling errors that affect earth-based radio metric data, such as errors in tracking station locations, the Martian ephemeris, and differences in the quasar and planetary coordinate frames, are improved, then perhaps earth-based tracking could meet the entry error requirements imposed by aerocapture. If not, then the other three options of intervehicular range, optical data, or differenced range provide highly accurate entry knowledge at least twelve hours before entry.

Konopliv, Alex↗
NASA NTRS1994

Galileo Orbit Determination During the Ida Encounter

As the time of the Ida encounter by Galileo approached, some unfortunate circumstances occurred, causing a very worrisome but exciting encounter, especially with regards to navigation. This paper reports on Galileo's orbit determination stratagy during the period after the last Earth encounter through the Ida flyby. Details in the modeling of Galileo's orbit, and in the use of various navigation tools, will be explained and the results of several key orbit solutions will be given.

Galileo Ida encounter orbit determination navigati↗
NASA NTRSDate not supplied

LuNaMaps FY 2024 Annual Program Review

The LuNaMaps project seeks to advance mapping capabilities and understanding in preparation for lunar landing scenarios. In this presentation we outline the advancements made by the team over the last year.

stereophotogrammetry↗
NASA NTRS1992

Deep-space navigation applications of improved ground-based optical astrometry

Improvements in ground-based optical astrometry will eventually be required for navigation of interplanetary spacecraft when these spacecraft communicate at optical wavelengths. Although such spacecraft may be some years off, preliminary versions of the astrometric technology can also be used to obtain navigational improvements for the Galileo and Cassini missions. This article describes a technology-development and observational program to accomplish this, including a cooperative effort with U.S. Naval Observatory Flagstaff Station. For Galileo, Earth-based astrometry of Jupiter's Galilean satellites may improve their ephemeris accuracy by a factor of 3 to 6. This would reduce the requirements for onboard optical navigation pictures, so that more of the data transmission capability (currently limited by high-gain antenna deployment problems) can be used for science data. Also, observations of European Space Agency (ESA) Hipparcos stars with asteroid 243 Ida may provide significantly improved navigation accuracy for a planned August 1993 Galileo spacecraft encounter.

Null, G. W.↗
NASA NTRS1984

Interplanetary navigation

The evolution of NASA's planetary navigation techniques is traced, and radiometric and optical data types are described. Doppler navigation; the Deep Space Network; differenced two-way range techniques; differential very long base interferometry; and optical navigation are treated. The Doppler system enables a spacecraft in cruise at high absolute declination to be located within a total angular uncertainty of 1/4 microrad. The two-station range measurement provides a 1 microrad backup at low declinations. Optical data locate the spacecraft relative to the target to an angular accuracy of 5 microrad. Earth-based radio navigation and its less accurate but target-relative counterpart, optical navigation, thus form complementary measurement sources, which provide a powerful sensory system to produce high-precision orbit estimates.

Stuart, J. R.↗
NASA NTRS2017

Optical-Based Kinematic Positioning for Deep-Space Navigation

NASA’s Deep Space 1 mission demonstrated that a spacecraft can be navigated autonomously during deep-space cruise operations using only images of distant asteroids as measurements. This paper derives an approximation of the position estimate accuracy that can be achieved with this technique based on the assumption of multiple, simultaneous line-of-sight measurements. This achievable accuracy is computed for locations across the solar system, which can be used to estimate cruise navigation performance as a function of spacecraft trajectory. It is shown that a on-board optical navigation system can achieve kinematic position estimate accuracies of better than 100 km throughout the inner solar system with a highperformance camera and from many hundred to several thousand kilometers with a low-end camera. Beyond the main-asteroid belt, the feasibilty of this approach suffers due to lack of targets. A case-study implementation of this approach for the upcoming InSight mission to Mars is also presented.

Bhaskaran, Shyam↗
NASA NTRS2010

Preliminary Design of the Guidance, Navigation, and Control System of the Altair Lunar Lander

Guidance, Navigation, and Control (GN&C) is the measurement and control of spacecraft position, velocity, and attitude in support of mission objectives. This paper provides an overview of a preliminary design of the GN&C system of the Lunar Lander Altair. Key functions performed by the GN&C system in various mission phases will first be described. A set of placeholder GN&C sensors that is needed to support these functions is next described. To meet Crew safety requirements, there must be high degrees of redundancy in the selected sensor configuration. Two sets of thrusters, one on the Ascent Module (AM) and the other on the Descent Module (DM), will be used by the GN&C system. The DM thrusters will be used, among other purposes, to perform course correction burns during the Trans-lunar Coast. The AM thrusters will be used, among other purposes, to perform precise angular and translational controls of the ascent module in order to dock the ascent module with Orion. Navigation is the process of measurement and control of the spacecraft's "state" (both the position and velocity vectors of the spacecraft). Tracking data from the Earth-Based Ground System (tracking antennas) as well as data from onboard optical sensors will be used to estimate the vehicle state. A driving navigation requirement is to land Altair on the Moon with a landing accuracy that is better than 1 km (radial 95%). Preliminary performance of the Altair GN&C design, relative to this and other navigation requirements, will be given. Guidance is the onboard process that uses the estimated state vector, crew inputs, and pre-computed reference trajectories to guide both the rotational and the translational motions of the spacecraft during powered flight phases. Design objectives of reference trajectories for various mission phases vary. For example, the reference trajectory for the descent "approach" phase (the last 3-4 minutes before touchdown) will sacrifice fuel utilization efficiency in order to provide landing site visibility for both the crew and the terrain hazard detection sensor system. One output of Guidance is the steering angle commands sent to the 2 degree-of-freedom (dof) gimbal actuation system of the descent engine. The engine gimbal actuation system is controlled by a Thrust Vector Control algorithm that is designed taking into account the large quantities of sloshing liquids in tanks mounted on Altair. In this early design phase of Altair, the GN&C system is described only briefly in this paper and the emphasis is on the GN&C architecture (that is still evolving). Multiple companion papers will provide details that are related to navigation, optical navigation, guidance, fuel sloshing, rendezvous and docking, machine-pilot interactions, and others. The similarities and differences of GN&C designs for Lunar and Mars landers are briefly compared.

Lee, Allan Y.↗
NASA NTRS1970

Guidance and Navigation Requirements for Unmanned Flyby and Swingby Missions to the Outer Planets: Low Thrust Missions, Phase B - Volume 3

The guidance and navigation requirements for unmanned missions to the outer planets, assuming constant, low thrust, ion propulsion are discussed. The navigational capability of the ground based Deep Space Network is compared to the improvements in navigational capability brought about by the addition of guidance and navigation related onboard sensors. Relevant onboard sensors include: (1) the optical onboard navigation sensor, (2) the attitude reference sensors, and (3) highly sensitive accelerometers. The totally ground based, and the combination ground based and onboard sensor systems are compared by means of the estimated errors in target planet ephemeris, and the spacecraft position with respect to the planet.

Source record↗
NASA NTRS1993

Calculating potential fields using microchannel spatial light modulators

We describe and present experimental results of the optical calculation of potential field maps suitable for mobile robot navigation. The optical computation employs two write modes of a microchannel spatial light modulator (MSLM). In one mode, written patterns expand spatially, and this characteristic is used to create an extended two dimensional function representing the influence of the goal in a robot's workspace. Distinct obstacle patterns are written in a second, non-expanding, mode. A model of the mechanisms determining MSLM write mode characteristics is developed and used to derive the optical calculation time for full potential field maps. Field calculations at a few hertz are possible with current technology, and calculation time vs. map size scales favorably in comparison to digital electronic computation.

Reid, Max B.↗
NASA NTRS1967

Star/horizon simulator used to test space guidance system

Star/horizon simulator is used for alignment and optical plus photoelectric tests of the sextant for the Apollo guidance and navigation system optical unit assembly. The unit is basically a refractive collimator with a two inch objective lens system and a twenty-four inch focal length.

Schmidt, W. C.↗
NASA NTRSDate not supplied

Machine Learning Based Crater Detection for Terrain Relative Navigation

As Lunar exploration continues to become more commonplace, reliable methods of precise Terrain Relative Navigation (TRN) are needed. While there are many TRN techniques available, one that has received increased interest in the past few years is that of crater based navigation. Crater based navigation has numerous benefits, including being a human recognizable feature (important for crewed missions), as well as the fact that craters are often possible hazards that need to be detected and avoided. The use of crater based navigation has been limited however. This has been due to the difficulty of running such algorithms on board a spacecraft, as well as the difficulty in procuring large amounts of the required training data. This paper presents a new rendering tool for generating large amounts of high quality training data. It then looks at two recently developed machine learning techniques for crater detection and crater identification in real-time on near-future space hardware.

computer vision↗
NASA NTRS2012

Autonomous Navigation Performance During The Hartley 2 Comet Flyby

On November 4, 2010, the EPOXI spacecraft performed a 700-km flyby of the comet Hartley 2 as follow-on to the successful 2005 Deep Impact prime mission. EPOXI, an extended mission for the Deep Impact Flyby spacecraft, returned a wealth of visual and infrared data from Hartley 2, marking the fifth time that high-resolution images of a cometary nucleus have been captured by a spacecraft. The highest resolution science return, captured at closest approach to the comet nucleus, was enabled by use of an onboard autonomous navigation system called AutoNav. AutoNav estimates the comet-relative spacecraft trajectory using optical measurements from the Medium Resolution Imager (MRI) and provides this relative position information to the Attitude Determination and Control System (ADCS) for maintaining instrument pointing on the comet. For the EPOXI mission, AutoNav was tasked to enable continuous tracking of a smaller, more active Hartley 2, as compared to Tempel 1, through the full encounter while traveling at a higher velocity. To meet the mission goal of capturing the comet in all MRI science images, position knowledge accuracies of +/- 3.5 km (3-?) cross track and +/- 0.3 seconds (3-?) time of flight were required. A flight-code-in-the-loop Monte Carlo simulation assessed AutoNav's statistical performance under the Hartley 2 flyby dynamics and determined optimal configuration. The AutoNav performance at Hartley 2 was successful, capturing the comet in all of the MRI images. The maximum residual between observed and predicted comet locations was 20 MRI pixels, primarily influenced by the center of brightness offset from the center of mass in the observations and attitude knowledge errors. This paper discusses the Monte Carlo-based analysis that led to the final AutoNav configuration and a comparison of the predicted performance with the flyby performance.

flyby↗