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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Titan Orbiter with Aerorover Mission (TOAM)

We propose to develop a new mission to Titan called Titan Orbiter with Aerorover Mission (TOAM). This mission is motivated by the recent discoveries of Titan, its atmosphere and its surface by the Huygens Probe, and a combination of in situ, remote sensing and radar mapping measurements of Titan by the Cassini orbiter. Titan is a body for which Astrobiology (i.e., prebiotic chemistry) will be the primary science goal of any future missions to it. TOAM is planned to use an orbiter and balloon technology (i.e., aerorover). Aerobraking will be used to put payload into orbit around Titan. The Aerorover will probably use a hot air balloon concept using the waste heat from the MMRTG approx. 500 watts. Orbiter support for the Aerorover is unique to our approach for Titan. Our strategy to use an orbiter is contrary to some studies using just a single probe with balloon. Autonomous operation and navigation of the Aerorover around Titan will be required, which will include descent near to the surface to collect surface samples for analysis (i.e., touch and go technique). The orbiter can provide both relay station and GPS roles for the Aerorover. The Aerorover will have all the instruments needed to sample Titan's atmosphere, surface, possible methane lakes-rivers, use multi-spectral imagers for surface reconnaissance; to take close up surface images; take core samples and deploy seismometers during landing phase. Both active and passive broadband remote sensing techniques will be used for surface topography, winds and composition measurements.

Sittler, Edward C.↗
NASA NTRS2007

Titan Orbiter with Aerorover Mission (TOAM)

We propose to develop a new mission to Titan called Titan Orbiter with Aerorover Mission (TOAM). This mission is motivated by the recent discoveries of Titan, its atmosphere and its surface by the Huygens Probe, and a combination of in situ, remote sensing and radar mapping measurements of Titan by the Cassini orbiter. Titan is a body for which Astrobiology (i.e., prebiotic chemistry) will be the primary science goal of any future missions to it. TOAM is planned to use an orbiter and balloon technology (i.e., aerorover). Aerobraking will be used to put payload into orbit around Titan. One could also use aerobraking to put spacecraft into orbit around Saturn first for an Enceladus phase of the mission and then later use aerocapture to put spacecraft into orbit around Titan. The Aerorover will probably use a hot air balloon concept using the waste heat from the MMRTG approx. 1000 watts. Orbiter support for the Aerorover is unique to our approach for Titan. Our strategy to use an orbiter is contrary to some studies using just a single probe with balloon. Autonomous operation and navigation of the Aerorover around Titan will be required, which will include descent near to the surface to collect surface samples for analysis (i.e., touch and go technique). The orbiter can provide both relay station and GPS roles for the Aerorover. The Aerorover will have all the instruments needed to sample Titan's atmosphere, surface, possible methane lakes-rivers, use multi-spectral imagers for surface reconnaissance; to take close up surface images; take core samples and deploy seismometers during landing phase. Both active and passive broadband remote sensing techniques will be used for surface topography, winds and composition measurements.

Sittler, E. C., Jr.↗
NASA NTRS2013

NASA Tech Briefs, April 2013

Topics covered include: Fully Integrated, Miniature, High-Frequency Flow Probe Utilizing MEMS Leadless SOI Technology; Nanoscale Surface Plasmonics Sensor With Nanofluidic Control; Advanced Dispersed Fringe Sensing Algorithm for Coarse Phasing Segmented Mirror Telescopes; Neural Network Back-Propagation Algorithm for Sensing Hypergols; Bulk Moisture and Salinity Sensor; Change-Based Satellite Monitoring Using Broad Coverage and Targetable Sensing; Circularly Polarized Microwave Antenna Element with Very Low Off-Axis Cross-Polarization; Ultra-Low Heat-Leak, High-Temperature Superconducting Current Leads for Space Applications; Flash Cracking Reactor for Waste Plastic Processing; An Automated Safe-to-Mate (ASTM) Tester; Wireless Chalcogenide Nanoionic-Based Radio-Frequency Switch; Compute Element and Interface Box for the Hazard Detection System; DOT Transmit Module; Composite Aerogel Multifoil Protective Shielding; Li-Ion Electrolytes with Improved Safety and Tolerance to High-Voltage Systems; Polymer-Reinforced, Non-Brittle, Lightweight Cryogenic Insulation; Controlled, Site-Specific Functionalization of Carbon Nanotubes with Diazonium Salts; Regenerable Sorbent for CO2 Removal; Sprayable Aerogel Bead Compositions With High Shear Flow Resistance and High Thermal Insulation Value; Lexan Linear Shaped Charge Holder with Magnets and Backing Plate; Robotic Ankle for Omnidirectional Rock Anchors; Wind, Wave, and Tidal Energy Without Power Conditioning; An Active Heater Control Concept to Meet IXO Type Mirror Module Thermal-Structural Distortion Requirement; Waterless Clothes-Cleaning Machine; Integrated Electrical Wire Insulation Repair System; LVGEMS Time-of-Flight Mass Spectrometry on Satellites; Surface Inspection Tool for Optical Detection of Surface Defects; Per-Pixel, Dual-Counter Scheme for Optical Communications; Certification-Based Process Analysis; Surface Navigation Using Optimized Waypoints and Particle Swarm Optimization; Smart-Divert Powered Descent Guidance to Avoid the Backshell Landing Dispersion Ellipse; Estimating Foreign-Object-Debris Density from Photogrammetry Data; Adaptive Sampling of Spatiotemporal Phenomena with Optimization Criteria; Building a 2.5D Digital Elevation Model From 2D Imagery; Eyes on the Earth 3D; Target Trailing With Safe Navigation for Maritime Autonomous Surface Vehicles; Adams-Based Rover Terramechanics and Mobility Simulator - ARTEMIS; ISTP CDF Skeleton Editor; Uplink Summary Generator (ULSGEN) Version 1.0; Robotics On-Board Trainer (ROBoT); Software Engineering Tools for Scientific Models; Automatic Data Filter Customization Using a Genetic Algorithm; Tracker Toolkit; Towards Efficient Scientific Data Management Using Cloud Storage; On a Formal Tool for Reasoning About Flight Software Cost Analysis; A Nanostructured Composites Thermal Switch Controls Internal and External Short Circuit in Lithium Ion Batteries; Spacecraft Crew Cabin Condensation Control; and Functional Near-Infrared Spectroscopy Signals Measure Neuronal Activity in the Cortex.

Source record↗
NASA NTRS2013

Robot Science Autonomy in the Atacama Desert and Beyond

Science-guided autonomy augments rovers with reasoning to make observations and take actions related to the objectives of scientific exploration. When rovers can directly interpret instrument measurements then scientific goals can inform and adapt ongoing navigation decisions. These autonomous explorers will make better scientific observations and collect massive, accurate datasets. In current astrobiology studies in the Atacama Desert we are applying algorithms for science autonomy to choose effective observations and measurements. Rovers are able to decide when and where to take follow-up actions that deepen scientific understanding. These techniques apply to planetary rovers, which we can illustrate with algorithms now used by Mars rovers and by discussing future missions.

robotic surface exploration↗
NASA NTRS2012

Experimental Validation of Pulse Phase Tracking for X-Ray Pulsar Based

Pulsars are a form of variable celestial source that have shown to be usable as aids for autonomous, deep space navigation. Particularly those sources emitting in the X-ray band are ideal for navigation due to smaller detector sizes. In this paper X-ray photons arriving from a pulsar are modeled as a non-homogeneous Poisson process. The method of pulse phase tracking is then investigated as a technique to measure the radial distance traveled by a spacecraft over an observation interval. A maximum-likelihood phase estimator (MLE) is used for the case where the observed frequency signal is constant. For the varying signal frequency case, an algorithm is used in which the observation window is broken up into smaller blocks over which an MLE is used. The outputs of this phase estimation process were then looped through a digital phase-locked loop (DPLL) in order to reduce the errors and produce estimates of the doppler frequency. These phase tracking algorithms were tested both in a computer simulation environment and using the NASA Goddard Space flight Center X-ray Navigation Laboratory Testbed (GXLT). This provided an experimental validation with photons being emitted by a modulated X-ray source and detected by a silicon-drift detector. Models of the Crab pulsar and the pulsar B1821-24 were used in order to generate test scenarios. Three different simulated detector trajectories were used to be tracked by the phase tracking algorithm: a stationary case, one with constant velocity, and one with constant acceleration. All three were performed in one-dimension along the line of sight to the pulsar. The first two had a constant signal frequency and the third had a time varying frequency. All of the constant frequency cases were processed using the MLE, and it was shown that they tracked the initial phase within 0.15% for the simulations and 2.5% in the experiments, based on an average of ten runs. The MLE-DPLL cascade version of the phase tracking algorithm was used in the varying frequency case. This resulted in tracking of the phase and frequency by the DPLL outputs in both the simulation and experimental environments. The crab pulsar was experimentally tested with a trajectory with a higher acceleration. In this case the phase error tended toward zero as the observation extended to 250 seconds and the doppler frequency error tended to zero in under 100 seconds.

Experimental↗
NASA NTRS2020

Golden Section Search for Single Beacon Homing

Exploration of Ocean Worlds requires a new type of mission to be developed, an ice penetrating submersible vehicle. Such a mission would present a number of new challenges, including long range autonomous under ice navigation. We have developed a method based on Golden Section Search for an AUV to home to a base station with a single range-only acoustic beacon and no absolute heading measurement capabilities. We demonstrate this method in simulation to home from 10km away to within 1km. Such capabilities would be required for a submersible to explore any substantial portion of the oceans on these Ocean Worlds.

Chien, Steve↗
NASA NTRSDate not supplied

From Simulation to Reality With Random Noise

The challenging environment of autonomous vehicle (AV) navigation necessitates certain functions be performed by deep neural networks. Optimizing these models involves collecting vast quantities of domain-specific training data and ensuring that the dataset is representative of expected conditions. High-fidelity simulation plays a vital role in making this process feasible, allowing a wide range of scenarios to be explored at low cost. However, learning from simulation introduces subtle biases into models, which can degrade real-world performance in unpredictable ways. This effect can be mitigated with learning schemes specialized to bridge distributional shifts (transfer learning). Given the complex nature of these methods, the underlying models, and their environments, meaningfully evaluating performance is notstraight forward. Many unrelated factors can effect an improvement in generalization accuracy, but a full ablation analysis is often difficult. To tease out signal from noise, it is necessary to understand how transfer learning performance is affected by noise itself. The goals of this paper are (i) to establish a domain randomization baseline for a simple classification transfer learning task and (ii) to validate the RRAV testbed as a platform for further research in sim-to-real learning. We generate imagery from a simulation of NASA Ames Research Center and train a small convolutional neural network (ConvNet) to classify position relative to a centerline. Further models are trained with different types of noise progressively added to the data. The models are deployed aboard the on-site test vehicle to test real-world performance. In our experiments, we find that such naive domain randomization raises sim-to-real accuracy from 64% to 79%, while training directly on real data yields an 89% accuracy ceiling. These results suggest that the isolated mechanism of domain randomization can significantly improve generalization.

simulation↗
NASA NTRS2001

The Integration, Testing and Flight of the EO-1 GPS

The Global Positioning System has long been hailed as the wave of the future for autonomous on-board navigation of low Earth orbiting spacecraft despite the fact that relatively few spacecraft have actually employed it for this purpose. While several missions operated out of the Goddard Space Flight Center have flown GPS receivers on board, the New Millenium Program (NMP) Earth Orbiting-1 (EO-1) spacecraft is the first to employ GPS for active, autonomous on-board navigation. Since EO-1 was designed to employ GPS as its primary source of the navigation ephemeris, special care had to be taken during the integration phase of spacecraft construction to assure proper performance. This paper is a discussion of that process: a brief overview of how the GPS works, how it fits into the design of the EO-1 Attitude Control System (ACS), the steps taken to integrate the system into the EO-1 spacecraft, the ultimate on-orbit performance during launch and early operations of the EO-1 mission and the performance of the on-board GPS ephemeris versus the ground based ephemeris. Conclusions will include a discussion of the lessons learned.

Quinn, David A.↗
NASA NTRS2013

Liaison-Supplemented Navigation of a Crewed Vehicle in a Lunar Halo Orbit

This paper offers an early examination of the challenges of navigating a crewed vehicle, with all of the associated unmodeled accelerations that arise from the crew's activities, in an orbit about the Earth-Moon L2 point. The combination of the unstable nature of libration orbits with the lack of acceleration knowledge makes the station keeping strategy challenging. It is found that a combination of ground tracking and satellite-to-satellite tracking produces the most favorable navigation accuracy. This paper examines the costs and benefits of applying LiAISON (Linked Autonomous Interplanetary Satellite Orbit Navigation) to a crewed mission in an unstable L2 orbit.

ARTEMIS↗
NASA NTRS2013

Navigating a Crewed Lunar Vehicle Using LiASION

This paper examines the benefits of navigating a crewed vehicle at the Moon using both ground tracking and satellite-to-satellite tracking, where the tracking satellite is stationed in a lunar halo orbit. Linked Autonomous Interplanetary Satellite Orbit Navigation (LiAISON) is a new technique that has been shown to dramatically improve the navigation of lunar satellites, libration orbiters, and Earth orbiting satellites using simple scalar satellite-to-satellite observations, such as range or Doppler. In this paper, LiAISON is applied to the problem of navigations a crewed vehicle in low lunar orbit. It has been found that adding LiAISON observations to a ground navigation solution improves the navigation enough to reduce the number of active ground tracking stations from six to three.

Linked Autonomous Interplanetary Satellite Orbit N↗
NASA NTRS2018

CubeX: A Compact X-Ray Telescope Enables Both X-Ray Fluorescence Imaging Spectroscopy and Pulsar Timing Based Navigation

This paper describes the benefits of a miniaturized X-ray telescope payload in the context of a lunar mission. The first part describes the payload in detail, the second part summarizes a small satellite mission concept that utilizes its compact form factor and performance. The CubeX instrument can be used for both X-ray fluorescence (XRF) imaging spectroscopy and X-ray pulsar timing based navigation (XNAV). Using our recent technological advances in X-ray optics and sensors, CubeX combines high angular resolution (<1 arcminutes) Miniature Wolter-I X-ray optics (MiXO) with a common focal plane consisting of high spectral resolution (<150 eV at 1 keV) CMOS X-ray sensors and a high timing resolution (< 1 usec) SDD X-ray sensor. This novel combination of the instruments enables both XRF measurements and XNAV operations without moving parts. The high angular resolution of the MiXO opens a wide range of orbital configurations for observation. Given that performance, the instrument has unprecedented small volume (~1×1×6U), mass (<6 kg), and power (<9W) requirements and opens a wide range of applications for a variety of targets and missions including NEOs and Martian moons. In this paper we illustrate one potential application for a lunar mission concept: The elemental composition of the Moon holds keys to understanding the origin and evolution of both the Moon and the Earth. X-ray fluorescence (XRF), induced either by solar X-ray flux or energetic ions, carries decisive signatures of surface elemental composition. X-ray observations, therefore, give a unique, powerful diagnostic tool for remotely determining elemental abundances including major rock forming elements such as Mg, Al, Na, Si, Fe, and Ca. Through high-resolution XRF imaging spectroscopy, CubeX searches for small patches of elusive lower crust and mantle material excavated within and around impact craters. CubeX identifies regional compositional variations and allows straightforward comparison of elemental distributions with the surface topography from LRO and the gravity data from GRAIL. The elemental compositions of the lower crust and the mantle are sensitive to the conditions of the giant impact which led to the Moon's formation and the subsequent lunar magma ocean (LMO), and thus they are key missing pieces in understanding the formation and early evolution of the Moon. In between XRF observations, CubeX also leverages the technology of high resolution X-ray imaging and time series measurements to conduct XNAV operations and evaluate their performance. Deep space navigation is a critical issue for small planetary missions. XNAV can enable low-cost autonomous deep-space navigation, and has the potential to greatly assist, or even outperform, NASA's Deep Space Network (DSN) or ESA's European Space Tracking (ESTRACK). CubeX is designed to perform sequential observations of 3-4 millisecond pulsars (MSPs) to solve the spacecraft trajectory for absolute navigation, and explore the remote sensing capability of XNAV. In the presented mission concept, the Moon's relative proximity enables a straightforward evaluation of the XNAV performance through DSN.

x-ray spectroscopy↗
DOE OSTI2026

Self-driving thin film laboratory: autonomous epitaxial atomic-layer synthesis via real-time computer vision analysis of electron diffraction

Emerging materials science platforms with the ability to make autonomous decisions on the fly are fundamentally changing the outlook and protocols for materials optimization and discovery. Because AI-driven self-navigating schemes can effectively reduce the total number of iterations needed to arrive at the "answer" (i.e. the best stochiometric composition for a desired physical property, optimum materials processing parameters, etc.) by significant margins, they have the potential to revolutionize materials and chemical manufacturing processes at large in research laboratory settings as well as in industrial plants. Here, we demonstrate a successful implementation of real-time closed-loop autonomous navigation of a multi-dimensional materials synthesis parameter space for fabricating phase-pure epitaxial films of a metastable phase of a functional oxide in a combinatorial pulsed laser deposition chamber. Sequential epitaxial growth iterations in search of the optimized recipe to stabilize the desired crystal phase were performed using frame-by-frame quantitative computer vision analysis of reflection high-energy electron diffraction (RHEED) images of the unit-cell level film being deposited. The autonomous scheme regularly resulted in > 30-fold reduction in the number of required experiments compared to a comprehensive mapping of the parameter space. The real-time workflow developed here can be readily extended to a variety of thin film synthesis platforms opening the door for self-driving atomic-level materials design as well as autonomous optimization of semiconductor manufacturing.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Free-Flight Terrestrial Rocket Lander Demonstration for NASA's Autonomous Landing and Hazard Avoidance Technology (ALHAT) System

The Autonomous Landing Hazard Avoidance Technology (ALHAT) Project is chartered to develop and mature to a Technology Readiness Level (TRL) of six an autonomous system combining guidance, navigation and control with terrain sensing and recognition functions for crewed, cargo, and robotic planetary landing vehicles. The ALHAT System must be capable of identifying and avoiding surface hazards to enable a safe and accurate landing to within tens of meters of designated and certified landing sites anywhere on a planetary surface under any lighting conditions. Since its inception in 2006, the ALHAT Project has executed four field test campaigns to characterize and mature sensors and algorithms that support real-time hazard detection and global/local precision navigation for planetary landings. The driving objective for Government Fiscal Year 2012 (GFY2012) is to successfully demonstrate autonomous, real-time, closed loop operation of the ALHAT system in a realistic free flight scenario on Earth using the Morpheus lander developed at the Johnson Space Center (JSC). This goal represents an aggressive target consistent with a lean engineering culture of rapid prototyping and development. This culture is characterized by prioritizing early implementation to gain practical lessons learned and then building on this knowledge with subsequent prototyping design cycles of increasing complexity culminating in the implementation of the baseline design. This paper provides an overview of the ALHAT/Morpheus flight demonstration activities in GFY2012, including accomplishments, current status, results, and lessons learned. The ALHAT/Morpheus effort is also described in the context of a technology path in support of future crewed and robotic planetary exploration missions based upon the core sensing functions of the ALHAT system: Terrain Relative Navigation (TRN), Hazard Detection and Avoidance (HDA), and Hazard Relative Navigation (HRN).

Rutishauser, David K.↗
NASA NTRS2012

Fully Self-Contained Vision-Aided Navigation and Landing of a Micro Air Vehicle Independent from External Sensor Inputs

Direct-lift micro air vehicles have important applications in reconnaissance. In order to conduct persistent surveillance in urban environments, it is essential that these systems can perform autonomous landing maneuvers on elevated surfaces that provide high vantage points without the help of any external sensor and with a fully contained on-board software solution. In this paper, we present a micro air vehicle that uses vision feedback from a single down looking camera to navigate autonomously and detect an elevated landing platform as a surrogate for a roof top. Our method requires no special preparation (labels or markers) of the landing location. Rather, leveraging the planar character of urban structure, the landing platform detection system uses a planar homography decomposition to detect landing targets and produce approach waypoints for autonomous landing. The vehicle control algorithm uses a Kalman filter based approach for pose estimation to fuse visual SLAM (PTAM) position estimates with IMU data to correct for high latency SLAM inputs and to increase the position estimate update rate in order to improve control stability. Scale recovery is achieved using inputs from a sonar altimeter. In experimental runs, we demonstrate a real-time implementation running on-board a micro aerial vehicle that is fully self-contained and independent from any external sensor information. With this method, the vehicle is able to search autonomously for a landing location and perform precision landing maneuvers on the detected targets.

autonomous landing↗
NASA NTRS2012

LiAISON-Supplemented Navigation for Geosynchronous and Lunar L1 Orbiter

A high-fidelity simulation is developed to test the theory that relative range and range-rate measurements between a satellite in a geosynchronous orbit and a satellite in orbit about the Earth-Moon L1 point may be used to improve the navigation accuracy of both satellites, compared with ground-only tracking. Recent research has determined that satellite-to-satellite range measurements between these two orbits are su cient to perform absolute state estimation as well as relative state estimation of both satellites - a technology known as LiAISON (Linked Autonomous Interplanetary Satellite Orbit Navigation). This study quanties the improvement in accuracy when LiAISON is used to supplement ground tracking of one or both satellites in a very realistic simulation. Orbit determination techniques show that the inclusion of LiAISON measurements with ground tracking observations can greatly improve absolute position and velocity estimates for both satellites in geosynchronous orbit and about the Earth-Moon L1 point.

satellite-to-satellite tracking (SST)↗
NASA NTRSDate not supplied

Reinforcement Learning for Spacecraft Navigation & Environment Characterization in the Planar-Restricted Two-Body Problem

As science, exploration, and commercial space missions become increasingly complex, so does the need for efficient, autonomous, and integrated spacecraft navigation and operations techniques. Key operational functions, including data collection and transmission, environment characterization, systems constraints, human factors, and navigation, often are intertwined and conflicted. Deep Reinforcement Learning (DRL) offers a framework for addressing integrated spacecraft navigation and planning in an uncertain dynamical environment. The goal of this study is to evaluate the utility of DRL for integrated spacecraft navigation and planning. This is achieved by developing a simple environmental characterization training environment in the Planar-Restricted 2-Body Problem (PR2BP), establishing benchmarks and heuristic baselines, and designing a previously unstudied Markov Decision Process (MDP) formulation. This MDP formulation enables the spacecraft DRL agents to appropriately balance navigation and actuation capabilities. The resulting DRL-derived policy exceeds a random or untrained policy and meets or exceeds the level of performance of a heuristic without actuation. In the process, valuable intuition is gained about the problem with insight into how DRL methods could scale to increasingly more realistic scenarios, including net-work design and training architectures, efficient state space representations, and methods for encouraging exploration in a parametric action space, among others.

navigation↗
NASA NTRS2008

Wind-Based Navigation of a Hot-air Balloon on Titan: A Feasibility Study

Current analysis of data streamed back to Earth by the Cassini spacecraft features Titan as one of the most exciting places in the solar system. NASA centers and universities around the US, as well as the European Space Agency, are studying the possibility of sending, as part of the next mission to this giant moon of Saturn, a hot-air balloon (Montgolfier-type) for further and more in-depth exploration. The basic idea would be to design a reliable, semi-autonomous, and yet cheap Montgolfier capable of using continuous flow of waste heat from a power source to lift the balloon and sustain its altitude in the Titan environment. In this paper we study the problem of locally navigating a hot-air balloon in the nitrogen-based Titan atmosphere. The basic idea is to define a strategy (i.e. design of a suitable guidance system) that allows autonomous and semi-autonomous navigation of the balloon using the available (and partial) knowledge of the wind structure blowing on the saturnian satellite surface. Starting from first principles we determined the appropriate thermal and dynamical models describing (a) the vertical dynamics of the balloon and (b) the dynamics of the balloon moving on a vertical plane (2-D motion). Next, various non-linear fuzzy-based control strategies have been evaluated, analyzed and implemented in MATLAB to numerically simulate the capability of the system to simultaneously maintain altitude, as well as a scientifically desirable trajectory. We also looked at the ability of the balloon to perform station keeping. The results of the simulation are encouraging and show the effectiveness of such a system to cheaply and effectively perform semiautonomous exploration of Titan.

balloon dynamics↗
NASA NTRS1980

Autonomous satellite orbit determination during the development phases of the global positioning system

An onboard navigation system was developed to aid the design and evaluation of algorithms used in autonomous satellite navigation with Global Positioning System (GPS) data. The performance of the algorithms designed for a GPS Receiver/Processor Assembly (R/PA) intended for LANDSAT-D was investigated during the development phases of the GPS (four to six satellites in the constellation). This evaluation emphasized the effects on the orbit determination accuracy of the expected user clock errors, GPS satellite visibility, force model approximations, and state and covariance propagation approximations. Results are presented giving the sensitivity of orbit determination accuracy to these constraints.

Dunham, J. B.↗