Search NASA⌕ Search

SEARCH · Search NASA

Results for “Navigation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 667 records · Page 37

Comparing Pre-Launch Assumptions to In-Flight Navigation Performance of OSIRIS-REx

The Sample Return Capsule (SRC) onboard the NASA Origins, Spectral Inter-pretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx)spacecraft is currently carrying samples of the B-type asteroid Bennu for safe re-turn to Earth at the Utah Test and Training Range on September 24, 2023. These samples were collected during the Touch And Go (TAG) sampling event on October 20, 2020, when the spacecraft contacted the surface for a few seconds at a location less than 1 meter from the target. The unprecedented navigation performance achieved during that event was the culmination of experience gained during two years of cruise and two years of increasingly challenging operation sat Bennu. As we had hoped, the proximity navigation performance at Bennu exceeded pre-launch analysis. This paper will compare the navigation performance through the proximity operation phases to our pre-launch analysis and will quantify how refinements of the small force models governing the spacecraft motion near Bennu considerably improved the down-track state predictions leading up to the successful TAG event. It was evident to the team and to expert peer reviewers during the design phase that exquisite model fidelity and aggressive operational concepts, which challenged and advanced the state of the art for deep space proximity operations, would be required to meet the mission’s objectives. This paper summarizes the superlative achievements of the team in rising to and overcoming these challenges.

Peter G Antresian↗

SCaN: Space Communication and Navigation - 5G in Space

NASA’s Space Communications and Navigation (SCaN) program office builds, operates, and maintains NASA’s two primary communications networks – the Near Space Network and the Deep Space Network. These networks allow spacecraft near and far to send critical tracking, telemetry, command, and science data to Earth. SCaN also investigates new communications and navigation technologies so that these networks can support advanced missions. SCaN’s Commercialization, Innovation, and Synergies (CIS) office is dedicated to creating robust partnerships with industry, academia, and other government agencies to advance communications and navigation capabilities.

5G↗

The Evolution of Deep Space Navigation: 2014–2016

The exploration of the planets of the solar system using robotic vehicles has been underway since the early 1960s. During this time the navigational capabilities employed have increased greatly in accuracy, as required by the scientific objectives of the missions and as enabled by improvements in technology. This paper is the eighth in a chronological sequence dealing with the evolution of deep space navigation. The time interval covered extends from 2014 to 2016. The paper focuses on the observational techniques that have been used to obtain navigational information, propellant-efficient means for modifying spacecraft trajectories, and the computational methods that have been employed, tracing their evolution through 11 planetary missions.

Wood, Lincoln J↗

Navigating Low-Energy Trajectories to Land on the Surface of Europa

The current interest in sending a probe to the surface of Europa in search of life demands not only efficient strategies in mission design, but also requires the capability of knowing the navigability of such types of trajectories. An initial search to find low-energy approach trajectories with a variety of topologies that are challenging to navigate is initially performed in the circular restricted three-body problem. These trajectories are subsequently converted to the ephemeris model and used for detailed navigation analysis. We explore several maneuver strategies and assess spacecraft state uncertainties at Europa arrival as well as fuel consumption.

McElrath, Tim↗

Navigation Performance Analysis and Trades for the Lunar GNSS Receiver Experiment (LuGRE)

The Lunar GNSS Receiver Experiment (LuGRE) is a joint NASA-Italian Space Agency flight demonstration payload that will fly onboard the Blue Ghost Mission 1 (BGM1) lunar lander to demonstrate multi-GNSS based position, navigation, and timing (PNT) in cislunar space and at the Moon. The LuGRE mission aims to receive GPS and Galileo signals at the Moon to characterize the lunar GNSS signal environment, demonstrate navigation and time estimation, and utilize collected data to support development of GNSS receivers specific to lunar use. Several key factors of the LuGRE design and concept of operations impact how navigation performance may be achieved during the mission, including available measurement observables, limited measurement duration, limited data rates, and use of a lower-quality oscillator. This paper investigates the impacts of these factors and how they may be exploited to inform mission design, and ultimately return the most interesting data possible.

GNSS↗

Hazard Boresight Relative Navigation for Safe Lunar Landing

In the area of planetary landing, hazard detection and avoidance is the act of driving a vehicle to a safe landing area using onboard resources. A hazard detection sensor is used to scan the terrain and these measurements are evaluated to determine where the safe landing sites are located. The selected site is generally not the same as the nominal target, so the vehicle must divert to the new site. This activity involves the interaction between several components, including a suite of onboard GNC algorithms that work together to efficiently choose and divert to a new site. This paper presents the Hazard Boresight Relative Navigation concept, which is a method that provides a common interface between the hazard scan, safe-site selection algorithm, size of the target-relative landing ellipse, divert offset distance and guidance targeting algorithm. After the safe-site is selected from the hazard scan, the original inertial target is replaced with a vehicle-relative target, which is initialized by a measurement from the hazard scan. The new target-relative position state is estimated over time in the navigation filter, and is fed to the guidance algorithm to perform the divert maneuver. In addition to detailing the Hazard Boresight Relative Navigation concept, this paper also presents some general landing terms that can be used in the greater discussion, as well as analysis on how to estimate and predict the vehicle footprint dispersion ellipse during flight, which is used in the safe-site selection algorithm.

Stephen R. Steffes↗

Hazard Boresight Relative Navigation for Safe Lunar Landing

In the area of planetary landing, hazard detection and avoidance is the act of driving a vehicle to a safe landing area using onboard resources. A hazard detection sensor is used to scan the terrain and these measurements are evaluated to determine where the safe landing sites are located. The selected site is generally not the same as the nominal target, so the vehicle must divert to the new site. This activity involves the interaction between several components, including a suite of onboard GNC algorithms that work together to efficiently choose and divert to a new site. This paper presents the Hazard Boresight Relative Navigation concept, which is a method that provides a common interface between the hazard scan, safe-site selection algorithm, size of the target-relative landing ellipse, divert offset distance and guidance targeting algorithm. After the safe-site is selected from the hazard scan, the original inertial target is replaced with a vehicle-relative target, which is initialized by a measurement from the hazard scan. The new target-relative position state is estimated over time in the navigation filter, and is fed to the guidance algorithm to perform the divert maneuver. In addition to detailing the Hazard Boresight Relative Navigation concept, this paper also presents some general landing terms that can be used in the greater discussion, as well as analysis on how to estimate and predict the vehicle footprint dispersion ellipse during flight, which is used in the safe-site selection algorithm.

Stephen Steffes↗

Navigation Performance of the BioSentinel Deep Space CubeSat Mission

The BioSentinel mission was recently launched aboard the SLS launch vehicle (LV) as part of the Artemis- 1 campaign. The BioSentinel navigation team successfully tracked and guided the spacecraft through a lunar gravity assist to its destination Earth-trailing heliocentric orbit. This 6U CubeSat carries live yeast cells to analyze the effects of radiation at large distances from Earth, becoming the first biological payload in Deep Space. Prelaunch activities included mission design updates, orbit determination rehearsals and the development of a tracking schedule in coordination with the Artemis-1 payload office and the Deep Space Network (DSN). An important influence on the trajectories of Artemis I secondaries was the uncertainty associated with deployment from the Interim Cryogenic Propulsion System (ICPS), the upper stage of the SLS LV. The ICPS was rotating at a rate of 1 rpm; there was also an uncertainty in the spin axis attitude, which translated into an unknown clock angle of deployment. The variability in this angle and magnitude of deployment implied the existence of a non-negligible risk of a lunar impact, which was evaluated for various potential launch dates. We present the results of Monte Carlo analyses and compute the pertinent maneuvers to avoid it. In addition, we present a comparison with the actual deployment once the mission launched by reconstructing our trajectory with tracking data. On November 16th 2022 BioSentinel successfully deployed from ICPS and the navigation team started to receive 2-way Doppler and Sequential Ranging data from the DSN. We processed early data to try to obtain a first ephemeris using Initial Orbit Determination (IOD) methods such as the least squares. Soon after deployment, the spacecraft was tumbling and entered safe mode, creating a period where the tracking data were sparse. The mission team recovered the spacecraft and after four tracking passes, we solved for a first ephemeris that was sent to the DSN for better tracking of the spacecraft. After propagating this first ephemeris solution, we determined that we avoided impact with a margin of a few hundred km from the lunar surface. More tracking data over the next few days (from DSN as well as ESA antennas) allowed for a more refined orbit solution predicting a periselene altitude of 406 km and a lunar eclipse lasting 36.5 minutes. Therefore, BioSentinel operators aborted any correction maneuvers. This periselene altitude also gave us the necessary energy to achieve a heliocentric orbit. The next challenge was due to the necessary adjustments in our orbit determination method due to the large energy boost resulting from the lunar flyby. After a series of tracking passes we were able to get a nominal solution that resulted into a stable trajectory. This paper discusses in detail the navigation performance using the X-band IRIS transponder, as well as the challenges and lessons learned prior to and during this deep space, CubeSat mission.

Andres Dono Perez↗

The Evolution of Deep Space Navigation: 2016-2018*

The exploration of the planets of the solar system using robotic vehicles has been underway since the early 1960s. During this time the navigational capabilities employed have increased greatly in accuracy, as required by the scientific objectives of the missions and as enabled by improvements in technology. This paper is the ninth in a chronological sequence dealing with the evolution of deep space navigation. The time interval covered extends from 2016 to 2018. The paper focuses on the observational techniques that have been used to obtain navigational information, propellant-efficient means for modifying spacecraft trajectories, and the computational methods that have been employed, tracing their evolution through 12 planetary missions.

Wood, Lincoln J.↗

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.↗

Real-World Testing of LiDAR-Inertial Based Navigation and Mapping for Precision Landing

The fusion of LiDAR and inertial measurements duringspacecraft descent and landing can be used to estimate alander’s navigation state and map the terrain below. Together,these data products can be used to enable safe and preciselanding on celestial bodies for which a priori orbital reconnaissanceis insufficient for hazard detection and avoidance.Unlike camera images used in visual terrain relative navigation,LiDAR scans are insensitive to changes in illumination; as aresult, the technique can be used to land in poorly lit areas,or at times of day when the lighting conditions are incongruentwith existing orbital imagery. In this paper, we extend previouswork in which we introduced a factor graph based smoothingapproach for LiDAR-inertial navigation and mapping. Whereasthe algorithms were previously tested on simulated data, thispaper presents testing on real-world data. Data from theAutonomous Landing Hazard Avoidance Technology (ALHAT)airplane flight tests in the Yucca Flats and Death Valley in2009 (FT3), the Morpheus vertical take off and landing flighttests at Kennedy Space Center in 2014 (FT6), and the landingof Perseverance and Ingenuity on Mars in 2021 (M2020) wereused to evaluate algorithm performance. In this paper, weextend our LiDAR-inertial technique to work with a variety ofranging technologies: single point laser altimetry (FT3), denseflash LiDAR (FT6), and six-beam radar (M2020). A thoroughperformance analysis for all three datasets is presented. Datasetpreparation, improvements in algorithm robustness, and outlierrejection, which were necessitated by the transition to realworlddata, are discussed.

Trawny, Nikolas↗

Navigation Sensor Technology Assessment Capability for Data-Driven Systems Analysis

The capability to assess the mission performance of novel navigation technologies from a systems-level approach and to provide quantitative results is crucial. With growing interest and innovations from NASA’s commercial partners, data-driven results that quantify the technological impact will guide research developments and facilitate stakeholder decision-making while requiring less time and resources. This paper presents a method to evaluate various sensor combinations and their impact on the overall system performance using an existing six degrees-of-freedom, physics-based engineering simulation for a government reference lunar lander as a testbed. Selected navigation technologies over various technology readiness levels, including Inertial Measurement Units, Navigation Doppler Lidar, and radar altimeter-radar velocimeter, were studied in this paper. Results using this testbed to perform sensitivity studies and to provide quantitative assessments are reported. One key finding is that there are diminishing returns for reducing sensor errors. The most influential sensor parameter to landing success are vehicle configuration and mission dependent. Results from this method could be used by stakeholders to make data-driven systems-based decisions and by technology developers as guidance for the specific parameter improvements that will have the most significant impact on mission success. This capability could be further used to assess alternative scenarios should one type of technology become unavailable or to re-assess initial assumptions and identify appropriate requirements from a system perspective.

Esther Lee↗

Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE) Pathfinder for Artemis Gateway

The Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE) mission was developed by NASA in collaboration with Advanced Space, LLC of Westminster, Colorado. This technology demonstration mission serves as a pathfinder for near rectilinear halo orbit (NHRO) operations around the Moon. The NHRO, (Perilune = 3,200 km; Apolune = 70,000 km) is the intended orbit for NASA’s Artemis Gateway, a small, human-tended space station planned for lunar orbit. The CAPSTONE mission will validate simulations and confirm operational planning for Gateway while also validating performance of navigation and station-keeping requirements for Gateway’s Power and Propulsion Element. Thus, this mission will provide operational experience to NASA, commercial, and international missions for operations in a demanding orbital regime. The CAPSTONE mission consists of a 12-unit (U) CubeSat developed, integrated, and tested by the Terran Orbital Corporation that carries a payload communications system capable of cross-link ranging with NASA’s Lunar Reconnaissance Orbiter (LRO). CAPSTONE contains a chip scale atomic clock (CSAC) for a one-way ranging experiment with NASA’s Deep Space Network, a dedicated payload flight computer for software demonstration, and a camera. The launch, coordinated by NASA’s Launch Services Program, was provided by Rocket Lab on its Electron launch vehicle utilizing their Photon upper stage to deploy the CAPSTONE spacecraft into lunar orbit. The mission launched June 28, 2022. The CAPSTONE spacecraft deployed from Rocket Lab’s Photon stage and traversed an approximately 4 month highly efficient transfer phase entering the NRHO Novermber 13, 2022 for a six-month primary mission phase. The mission is currently in a twelve-month technology enhancement operations phase. The CAPSTONE technology demonstration mission is lead by Advanced Space, LLC. Spacecraft development and mission operations is conducted by Terran Orbital Corporation of Irvine, California. Noted accomplishments for the CAPSTONE mission include demonstration of the accessibility of NHROs, validation of key operational concepts in the NHRO environment, laying the foundation for commercial support of future lunar operations, and accelerating the availability of peer-to-peer navigation capabilities provided by the Cislunar Autonomous Positioning System (CAPS). The CAPSTONE mission is funded through NASA's Small Spacecraft Technology (SST) program, which is one of several programs within NASA’s Space Technology Mission Directorate. The program is chartered to develop and demonstrate technologies to enhance and expand the capabilities of small spacecraft with a particular focus on enabling new mission architectures through the use of small spacecraft, expanding the reach of small spacecraft to new destinations, and augmenting future missions with supporting small spacecraft. The CAPSTONE mission launch was provided by NASA’s Exploration Systems Development Missions Directorate’s Advanced Exploration Systems Division. Coordination and acquisition of the launch was managed by NASA’s Launch Services Program. The CAPSTONE mission and project status will be presented.

Elwood Agasid↗

Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE) Pathfinder for Artemis Gateway

The Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment (CAPSTONE) mission was developed by NASA in collaboration with Advanced Space, LLC of Westminster, Colorado. This technology demonstration mission serves as a pathfinder for near rectilinear halo orbit (NHRO) operations around the Moon. The NHRO, (Perilune = 3,200 km; Apolune = 70,000 km) is the intended orbit for NASA’s Artemis Gateway, a small, human-tended space station planned for lunar orbit. The CAPSTONE mission will validate simulations and confirm operational planning for Gateway while also validating performance of navigation and stationkeeping requirements for Gateway’s Power and Propulsion Element. Therefore, this mission will provide operational experience to NASA, commercial, and international missions for operations in a demanding orbital regime. The CAPSTONE mission consists of a 12-unit (U)+ CubeSat developed, integrated, and tested by the Terran Orbital Corporation that carries a payload communications system capable of crosslink ranging with NASA’s Lunar Reconnaissance Orbiter (LRO). CAPSTONE contains a chip-scale atomic clock (CSAC) for a one-way ranging experiment with NASA’s Deep Space Network, a dedicated payload flight computer for software demonstration, and a camera. The launch, coordinated by NASA’s Launch Services Program, was provided by Rocket Lab on its Electron launch vehicle using their Photon upper stage to deploy the CAPSTONE spacecraft. The mission launched June 28, 2022. The CAPSTONE spacecraft deployed from the Photon stage and traversed an approximately 4-month, highly fuel-efficient transfer phase entering the NRHO November 13, 2022, for a six-month primary mission phase. The mission is currently in a twelve-month technology enhancement operations phase. The CAPSTONE technology demonstration mission is led by Advanced Space, LLC. Spacecraft development and mission operations are conducted by Terran Orbital Corporation of Irvine, California. Noted accomplishments for the CAPSTONE mission include demonstrating the accessibility of NHROs; validating key operational concepts in the NHRO environment; laying the foundation for commercial support of future lunar operations; and accelerating the availability of peer-to-peer navigation capabilities provided by the Cislunar Autonomous Positioning System (CAPS). The CAPSTONE mission is funded through NASA’s Small Spacecraft Technology (SST) program, which is one of several programs within NASA’s Space Technology Mission Directorate. The program is chartered to develop and demonstrate technologies to enhance and expand the capabilities of small spacecraft with a particular focus on enabling new mission architectures through the use of small spacecraft, expanding the reach of small spacecraft to new destinations, and augmenting future missions with supporting small spacecraft. The CAPSTONE mission launch was provided by NASA’s Exploration Systems Development Missions Directorate’s Advanced Exploration Systems Division. Coordination and acquisition of the launch was managed by NASA’s Launch Services Program. The CAPSTONE mission and project status will be presented.

Elwood Agasid↗

Goddard Enhanced Onboard Navigation System (GEONS) Mathematical Specifications

The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) has developed the capability to provide high-accuracy attitude, orbit, and time autonomously onboard NASA spacecraft. The GSFC Mission Engineering and Systems Analysis Division has implemented NASA-developed navigation algorithms for high-accuracy real-time onboard orbit determination in the Global Positioning System (GPS) Enhanced Orbit Determination (GEODE) flight software. The Goddard Enhanced Onboard Navigation System (GEONS) extends the capabilities of the GEODE flight software to include additional measurement types and additional navigation algorithms.

Anne C. Long↗

First Demonstration of Simultaneous Ranging and Velocimetry With Coherent Lidar on the Moon With NASA'S Navigation Doppler Lidar

A coherent Doppler lidar, referred to as Navigation Doppler Lidar (NDL), has been developed at NASA Langley Research Center for providing simultaneous but independent precision velocity and altitude measurements to a spacecraft’s navigation system during the final stages of landing, starting at approximately 5 km altitude. Onboard the Intuitive Machines NOVA-C lunar lander (also known as Odysseus), NDL provided fully reliable measurements within its intended operational range without any false alarms and demonstrated the sensitivity of coherent lidar by measuring velocity and range to the ground from up to 10 km altitude. The data collected during this mission illustrates the capability of NDL for future lunar and interplanetary missions, enhancing navigation accuracy and safety.

FMCW lidar↗

Terrain-Relative Navigation with Neuro-Inspired Elevation Encoding

Terrain-relative navigation (TRN) encompasses a wide variety of algorithms that perform localization with respect to the terrain below a flying vehicle. In traditional approaches, measurements of the terrain are matched to a map carried onboard. This work presents a terrain-relative navigation filter with a position measurement inspired by neural activity associated with positioning in nature. Here, the filter is shown to produce accurate position measurements that outperform popular optimization and template matching methods given poor prior knowledge of the position. The proposed method is also better-suited to distributed implementation than optimization-based methods.

33 ADVANCED PROPULSION SYSTEMS↗