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NASA NTRSDate not supplied

Multi-Functional Flash Lidar for Precision Safe Landing in Challenging Terrains

A Flash Lidar utilizing a novel Super-Resolution (SR) technique has been developed for providing Terrain Relative Navigation and Hazard Avoidance capabilities onboard landing vehicles. Processing algorithms for precision navigation and safe landing location identification take advantage of the uniform fixed pixels property of generated high resolution Digital Elevation Maps (DEMs) to achieve high reliability operation in near real-time. This paper describes the current and next generation breadboard units, report the results of recent dynamic tests, and explain the operational concept as envisioned for future landing missions.

3-D Imaging↗

NASA NTRSDate not supplied

Lunar Navigation Performance Using the Deep Space Network and Alternate Solutions to Support Precision Landing

As human exploration once again targets the surface of the Moon, questions continue to emerge regarding the necessity of Earth-based tracking systems, such as the Deep Space Network, for spacecraft navigation in support of lunar descent and landing. This paper will derive an extensive Deep Space Network sensor model for use in linear covariance analysis and demonstrate the resulting trajectory dispersions and navigation performance in comparison with alternate solutions, such as terrain relative navigation. An in-depth trade study with considerations for various trajectory profiles, time allocated to ground tracking, number of active ground stations, and interaction with other sensors will be conducted to shed significant insight into sensor suite requirements to ensure safe and precise landing on the Moon.

Navigation↗

NASA NTRSDate not supplied

Celestial Navigation in Cislunar Space with autoNGC

Celestial navigation (CelNav) is a source of navigation observables where images of known solar system bodies are used to locate a spacecraft, beneficial within the solar system for both cislunar and deep space missions. CelNav provides a variety of design benefits to support and enable current and new autonomous space operations- using only a camera and a processor to produce in-situ measurements for navigation. This technology reduces subscription to ground-based tracking during all phases of a mission, freeing up resources for other operational needs. This also supports secure navigation since it eliminates the need for ground contact. CelNav enables missions where the light time delay between Earth and the spacecraft is too long (or the Earth to spacecraft line of sight is obscured) to support critical operations. It also enables smaller mission classes, where Deep Space Network (DSN)time is cost prohibitive, to reduce its cost by focusing primarily on data downlink. Finally, it enables the NASA Artemis program and other cislunar human space flight by providing redundant navigation to traditional radiometric tracking. In this presentation, we discuss the implementation of a CelNav app in autonomous Navigation, Guidance, and Control (autoNGC), a comprehensive flight software suite for onboard autonomy that is built on the core Flight System (cFS). The presentation also summarizes the results of flight software-in-the-loop (SIL) and processor-in-the-loop (PIL) demonstrations. Both are high-fidelity simulations with the use of a camera emulator hosted on a GPU server that simulates images that would be captured by the camera. The CelNav app leverages the use of cGIANT (cFS Goddard Image Analysis and Navigation Tool).Previously developed for the autoNGC software suite, cGIANT is an onboard autonomous image processing and optical navigation (OpNav) tool that performs limb-based OpNav and Terrain Relative Navigation. The added CelNav capability of cGIANT generates bearing measurements to multiple known celestial bodies (planets, moons, asteroids, comets, etc.) in monocular (2D) images. These observables are then fed to the Goddard Enhanced Onboard Navigation System (GEONS)navigation filter app, enabling us to navigate the spacecraft autonomously. In early 2025, the autoNGC CelNav capability is planned to be flight tested as part of the onboard autonomy experiment on the Cislunar Autonomous Positioning System Technology Operations and Navigation Experiment(CAPSTONE) spacecraft that is currently in a Lunar Near Rectilinear Halo Orbit(NRHO).

celestial navigation↗

NASA NTRSDate not supplied

Autonomous Navigation of a Lunar Relay Using GNSS and Other Measurements

Many of the highest priority destinations at the Moon lack a continuous view of Earth, such as the lunar poles or lunar far side. Exploration of these sites will require spacecraft in cislunar space to relay communications and provide position, navigation, and timing (PNT) services. Accurate knowledge of relay position, velocity, and time is essential to these services. This paper describes a concept for a PNT Instrument being developed for the Lunar Communications Relay and Navigation Systems (LCRNS) Project. The instrument is intended as a payload that would enable autonomous, on-board, real-time navigation and timing using Global Navigation Satellite System (GNSS), optical navigation, and one-way measurements from Earth-based ground stations. Hardware-in-the-loop simulations using flight software are used to realistically characterize performance on hardware platforms with a path to flight. These results provide preliminary validation of the proposed PNT Instrument, demonstrate the benefits of augmenting GNSS with other measurements, and serve as an insightful reference for the design of future lunar missions, including those that will operate within the LunaNet framework of standards. This instrument concept relies on several technologies developed at NASA Goddard Space Flight Center (GSFC). For GNSS observables, the instrument relies on the high-altitude NavCube 3 mini (NC3m) GNSS receiver specifically designed for cislunar applications. The autoNGC system, which consists of flight software and a hardware platform, is responsible for fusing the observables using its extended Kalman filter, the Goddard Enhanced Onboard Navigation System (GEONS). Optical navigation observables are processed within autoNGC (“autonomous Navigation, Guidance, and Control”) using the Goddard Image Analysis & Navigation Tool (GIANT) which is also responsible for simulating high-fidelity images for test and analysis. In addition to describing the PNT Instrument and its components, the paper will present predicted performance based on simulation results. As a baseline, it will present GNSS-only hardware-in-the loop results using a NC3m test unit to process Spirent-simulated GPS signals in a potential lunar relay trajectory: a 12-hour elliptical frozen lunar orbit (ELFO). GEONS then processes the GPS pseudorange and time differenced carrier phase measurements to estimate and propagate the relay state (position, velocity, and time). These results extend previously published work that showed preliminary ELFO performance. Previous work has shown the importance of other measurement types, so additional simulations are performed which augment GNSS with ground station observables and several methods of optical navigation, including celestial navigation, limb-finding (e.g., observations of the lunar horizon), and terrain relative navigation (TRN). TRN involves correlating simulated predicted images of the lunar surface with actual imagery; misalignments of landmarks identified in each image are translated into relay state updates. TRN is valuable as a measurement of the relay’s state relative to the Moon, especially during GNSS outages or after maneuvers. One-way Pseudorange and Doppler measurements from Earth-based ground stations are also simulated. The full set of observables is processed using autoNGC. These simulations make use of autoNGC and NC3m test units, a lab atomic clock, and a pulse-per-second (PPS) generation and distribution system. This combination of subsystems, and the hardware platforms used in this analysis, represents a PNT Instrument that could be flown on a lunar relay. Results from the hardware-in-the-loop simulations presented in this paper provide a preliminary assessment of the achievable navigation performance of this instrument concept. PNT Instrument performance is compared to the GPS-only performance, and a discussion is provided on the apparent merits and challenges of each measurement type.

Ben Ashman↗

NASA NTRS2019

Enabling repeat-pass interferometry from low Venus orbit

Repeat-pass interferometry is a powerful technique for determining changes in topography by flying a radar over the terrain two or more times. These overflights must be very close to each other in space. To design and maintain a low Venus orbit that enables this requires the consideration of drag, non-spherical gravity effects, and solar tides. Once the orbit is designed, the spacecraft must be navigated. To do so requires the use of radar-based terrain-relative navigation in addition to the traditional radiometric datatypes. The mission design and navigation to enable repeat-pass interferometry at Venus are described.

Hensley, Scott↗

NASA NTRS2019

Enabling repeat-pass interferomtetry from low Venus orbit

Hensley, Scott↗

NASA NTRS2017

Open-Loop Flight Testing of COBALT GN&C Technologies for Precise Soft Landing

A terrestrial, open-loop (OL) flight test campaign of the NASA COBALT (CoOperative Blending of Autonomous Landing Technologies) platform was conducted onboard the Masten Xodiac suborbital rocket testbed, with support through the NASA Advanced Exploration Systems (AES), Game Changing Development (GCD), and Flight Opportunities (FO) Programs. The COBALT platform integrates NASA Guidance, Navigation and Control (GN&C) sensing technologies for autonomous, precise soft landing, including the Navigation Doppler Lidar (NDL) velocity and range sensor and the Lander Vision System (LVS) Terrain Relative Navigation (TRN) system. A specialized navigation filter running onboard COBALT fuzes the NDL and LVS data in real time to produce a precise navigation solution that is independent of the Global Positioning System (GPS) and suitable for future, autonomous planetary landing systems. The OL campaign tested COBALT as a passive payload, with COBALT data collection and filter execution, but with the Xodiac vehicle Guidance and Control (G&C) loops closed on a Masten GPS-based navigation solution. The OL test was performed as a risk reduction activity in preparation for an upcoming 2017 closed-loop (CL) flight campaign in which Xodiac G&C will act on the COBALT navigation solution and the GPS-based navigation will serve only as a backup monitor.

Carson, John M., III↗

NASA NTRS2015

ALHAT COBALT: CoOperative Blending of Autonomous Landing Technology

The COBALT project is a flight demonstration of two NASA ALHAT (Autonomous precision Landing and Hazard Avoidance Technology) capabilities that are key for future robotic or human landing GN&C (Guidance, Navigation and Control) systems. The COBALT payload integrates the Navigation Doppler Lidar (NDL) for ultraprecise velocity and range measurements with the Lander Vision System (LVS) for Terrain Relative Navigation (TRN) position estimates. Terrestrial flight tests of the COBALT payload in an open-loop and closed-loop GN&C configuration will be conducted onboard a commercial, rocket-propulsive Vertical Test Bed (VTB) at a test range in Mojave, CA.

Carson, John M.↗

NASA NTRS2020

EDL Simulation Results for the Mars 2020 Landing Site Safety Assessment

The Mars 2020 rover is NASA’s next flagship mission, set to explore Mars in search of scientific evidence of past microbial life. Importantly, the rover will also, for the first time, have the ability to collect and cache rock and soil samples for retrieval and return to laboratories here on Earth. A key step in the development of the Mars 2020 mission is the selection of a suitable landing site with the largest likelihood of meeting scientific goals. This decision is a complex and critical one that requires close interaction between the scientific and engineering communities. The chosen landing site must be both scientifically interesting — providing the project with the greatest possible chance of gathering credible and defendable scientific evidence — and also safe enough to attempt a landing in the first place. Thus, arguably one of the most important undertakings of the Entry, Descent, and Landing (EDL) team, is to effectively enumerate, quantify, and communicate the landing risks to all of the stakeholders. The culmination of this effort is the Landing Site Safety Assessment, which is a review commissioned by the project, presided over by the EDL Standing Review Board, and attended by management and science stakeholders, in which the EDL team communicates their assessment of the associated landing risks and the statistical probability of a successful landing at each of the final candidate landing sites. This paper summarizes the results of high-fidelity computer simulations of the Mars 2020 EDL sequence used in this assessment. From an EDL performance perspective, all four candidates offer similar level of robustness, which is in-family with Mars Science Laboratory (MSL). However, two new features of the Mars 2020 EDL sequence – range trigger and Terrain-Relative Navigation (TRN) – dramatically enhance the capability of the EDL system to safely land at landing sites with much more rugged terrain than ever before considered. This has allowed the landing site selection for Mars 2020 to proceed in a manner that has been unprecedentedly weighted more heavily toward scientific interest and less heavily on engineering constraints. With TRN, the overall probability of success is predicted to be approximately 99% for all of the candidates.

David Way↗

NASA NTRS2016

GN and C Subsystem Concept for Safe Precision Landing of the Proposed Lunar MARE Robotic Science Mission

The Lunar MARE (Moon Age and Regolith Explorer) Discovery Mission concept targets delivery of a science payload to the lunar surface for sample collection and dating. The mission science is within a 100-meter radius region of smooth lunar maria terrain near Aristarchus crater. The location has several small, sharp craters and rocks that present landing hazards to the spacecraft. For successful delivery of the science payload to the surface, the vehicle Guidance, Navigation and Control (GN&C) subsystem requires safe and precise landing capability, so design infuses the NASA Autonomous precision Landing and Hazard Avoidance Technology (ALHAT) and a gimbaled, throttleable LOX/LCH4 main engine. The ALHAT system implemented for Lunar MARE is a specialization of prototype technologies in work within NASA for the past two decades, including a passive optical Terrain Relative Navigation (TRN) sensor, a Navigation Doppler Lidar (NDL) velocity and range sensor, and a Lidar-based Hazard Detection (HD) sensor. The landing descent profile is from a retrograde orbit over lighted terrain with landing near lunar dawn. The GN&C subsystem with ALHAT capabilities will deliver the science payload to the lunar surface within a 20-meter landing ellipse of the target location and at a site having greater than 99% safety probability, which minimizes risk to safe landing and delivery of the MARE science payload to the intended terrain region.

MARE (Moon Age and Regolith Explorer)↗

NASA NTRS2017

Guidance, Navigation and Control for the Entry, Descent, and Landing of the Mars 2020 Mission

This paper presents an overview of the Guidance, Navigation and Control (GNC) system for the Entry, Descent, and Landing (EDL) phases of the Mars 2020 Mission. The EDL GNC system adds Terrain Relative Navigation to the MSL EDL GNC system1 to enable landing on landing sites with landing hazards within the landing ellipse. This paper describes the GNC architecture, including sensors, actuators and algorithms, for the entry, parachute descent, and powered flight phases of the mission.

Brugarolas, Paul↗

NASA NTRSDate not supplied

Post-Flight Performance Analysis of Navigation and Advanced Guidance Algorithms on a Terrestrial Suborbital Rocket Flight

There is currently renewed interest in robotic and crewed landers for a return to the lunar surface. Advanced guidance and navigation algorithms are essential to accurately delivering cargo and crew safely to the moon successfully. This paper reports the overall performance of an integrated set of navigation and guidance algorithms flown on a terrestrial suborbital rocket up to an altitude of approximately 100km. The navigation algorithm consists of an onboard extended Kalman Filter (EKF) that ingests multiple sensor measurements, one of which is the output from a terrain relative navigation (TRN) algorithm that cross-references camera images to on-board satellite imagery to perform feature correlation within the camera image. The guidance algorithm solves for a 6-degree-of-freedom (DoF) optimal trajectory using a successive convexification method during powered descent. The altitude range as well as the landing dynamics experienced during this test flight are realistic for an extraterrestrial landing and provide an invaluable data set to gauge the current development of these landing algorithms in an effort to advance the overall software readiness levels (SRL). This paper will delve into different aspects of each algorithm and present an analysis of the in-flight performance of the algorithms. This flight was conducted under the National Aeronautics and Space Administration (NASA) Safe and Precise Landing Integrated Capabilities Evolution (SPLICE) project focused on technology advancement for landing applications.

Guidance↗

NASA NTRS2018

Cobalt: Terrestrial Flight Test of Landing Navigation Using Lander Vision System with Navigation Doppler Lidar

COBALT (CoOperative Blending of Autonomous Landing Technologies) is a NASA technology development and test program to advance precision landing capabilities for future soft landers. The COBALT payload demonstrated terrain relative navigation utilizing the Lander Vision System and Navigation Doppler Lidar sensors on the Masten Space Systems Xodiac rocket. In spring 2017, the program culminated in two open-loop free flights to 500 m altitude with downrange diverts of 300 m. The COBALT system performed well, navigating within meters of the Xodiac vehicle’s GPS-based solution. This paper outlines details of the navigation filter and its performance during the test campaign.

Carson, John M. III↗

NASA NTRS2016

COBALT: A GN&C Payload for Testing ALHAT Capabilities in Closed-Loop Terrestrial Rocket Flights

The COBALT (CoOperative Blending of Autonomous Landing Technology) payload is being developed within NASA as a risk reduction activity to mature, integrate and test ALHAT (Autonomous precision Landing and Hazard Avoidance Technology) systems targeted for infusion into near-term robotic and future human space flight missions. The initial COBALT payload instantiation is integrating the third-generation ALHAT Navigation Doppler Lidar (NDL) sensor, for ultra high-precision velocity plus range measurements, with the passive-optical Lander Vision System (LVS) that provides Terrain Relative Navigation (TRN) global-position estimates. The COBALT payload will be integrated onboard a rocket-propulsive terrestrial testbed and will provide precise navigation estimates and guidance planning during two flight test campaigns in 2017 (one open-loop and closed- loop). The NDL is targeting performance capabilities desired for future Mars and Moon Entry, Descent and Landing (EDL). The LVS is already baselined for TRN on the Mars 2020 robotic lander mission. The COBALT platform will provide NASA with a new risk-reduction capability to test integrated EDL Guidance, Navigation and Control (GN&C) components in closed-loop flight demonstrations prior to the actual mission EDL.

Carson, John M., III↗

NASA NTRS2016

COBALT CoOperative Blending of Autonomous Landing Technology

COBALT is a terrestrial test platform for development and maturation of GN&C (Guidance, Navigation and Control) technologies for PL&HA (Precision Landing and Hazard Avoidance). The project is developing a third generation, Langley Navigation Doppler Lidar (NDL) for ultra-precise velocity and range measurements, which will be integrated and tested with the JPL Lander Vision System (LVS) for Terrain Relative Navigation (TRN) position estimates. These technologies together provide navigation that enables controlled precision landing. The COBALT hardware will be integrated in 2017 into the GN&C subsystem of the Xodiac rocket-propulsive Vertical Test Bed (VTB) developed by Masten Space Systems (MSS), and two terrestrial flight campaigns will be conducted: one open-loop (i.e., passive) and one closed-loop (i.e., active).

Carson, John M. III↗

NASA NTRS2010

Autonomous GN and C for Spacecraft Exploration of Comets and Asteroids

A spacecraft guidance, navigation, and control (GN&C) system is needed to enable a spacecraft to descend to a surface, take a sample using a touch-and-go (TAG) sampling approach, and then safely ascend. At the time of this reporting, a flyable GN&C system that can accomplish these goals is beyond state of the art. This article describes AutoGNC, which is a GN&C system capable of addressing these goals, which has recently been developed and demonstrated to a maturity TRL-5-plus. The AutoGNC solution matures and integrates two previously existing JPL capabilities into a single unified GN&C system. The two capabilities are AutoNAV and GREX. AutoNAV is JPL s current flight navigation system, and is fairly mature with respect to flybys and rendezvous with small bodies, but is lacking capability for close surface proximity operations, sampling, and contact. G-REX is a suite of low-TRL algorithms and capabilities that enables spacecraft operations in close surface proximity and for performing sampling/contact. The development and integration of AutoNAV and G-REX components into AutoGNC provides a single, unified GN&C capability for addressing the autonomy, close-proximity, and sampling/contact aspects of small-body sample return missions. AutoGNC is an integrated capability comprising elements that were developed separately. The main algorithms and component capabilities that have been matured and integrated are autonomy for near-surface operations, terrain-relative navigation (TRN), real-time image-based feedback guidance and control, and six degrees of freedom (6DOF) control of the TAG sampling event. Autonomy is achieved based on an AutoGNC Executive written in Virtual Machine Language (VML) incorporating high-level control, data management, and fault protection. In descending to the surface, the AutoGNC system uses camera images to determine its position and velocity relative to the terrain. This capability for TRN leverages native capabilities of the original AutoNAV system, but required advancements that integrate the separate capabilities for shape modeling, state estimation, image rendering, defining a database of onboard maps, and performing real-time landmark recognition against the stored maps. The ability to use images to guide the spacecraft requires the capability for image-based feedback control. In Auto- GNC, navigation estimates are fed into an onboard guidance and control system that keeps the spacecraft guided along a desired path, as it descends towards its targeted landing or sampling site. Once near the site, AutoGNC achieves a prescribed guidance condition for TAG sampling (position/orientation, velocity), and a prescribed force profile on the sampling end-effector. A dedicated 6DOF TAG control then implements the ascent burn while recovering from sampling disturbances and induced attitude rates. The control also minimizes structural interactions with flexible solar panels and disallows any part of the spacecraft from making contact with the ground (other than the intended end-effector).

Carson, John M.↗

NASA NTRS2020

Encealdus Orbilander: A Flagship Mission Concept for Astrobiology

"Whether life exists beyond Earth remains a fundamental question driving our exploration of the Solar System. At Saturn’s moon Enceladus, plumes of oceanic material vented into space allow the investigation of the astrobiological potential of an ocean world, hinted at by Cassini, without the necessity of drilling through kilometers of ice crust. The Enceladus Orbilander is a flagship ($2.56B in fiscal year 2025 dollars) mission concept created for the 2023–2033 Planetary Science Decadal Survey. Orbilander takes full advantage of the opportunity provided by Enceladus’ plumes to search for signs of life. A single spacecraft both orbits and lands, capturing samples from four distinct reservoirs offered by the plumes. These samples, both particulate and vapor, are then analyzed by the Life Detection Suite (LDS), a set of five instruments conducting complementary and orthogonal biosignature-seeking measurements. To provide the context that specifically enhances interpretation of LDS measurements, geochemical and geophysical investigations are conducted both in orbit and on the surface. These reveal the physio-chemical state of the ocean and core as well as the processes involved in ejection of plume material and how these affect the ocean material analyzed by the LDS. The Orbilander can be delivered to the Saturn system via several launch vehicle and trajectory options, including a direct trajectory (7-year cruise), a ∆V-EGA trajectory (9-year cruise) and several options using an inner cruise with Venus and Earth flybys (10-year cruise). Upon Saturn Orbit Insertion, a 4-year moon tour pumps down the Orbilander’s orbit to intercept Enceladus. The most optimal arrival times balance the Jupiter flyby opportunities of the late 2030s and solar illumination at the Enceladus high southern latitudes where plume material is most abundant. This mission concept therefore targets project start in 2030. Upon Enceladus Orbit Insertion, the Orbilander begins a 1.5-year-long campaign of landing site reconnaissance, remote sensing science, and collecting sufficient plume sample to run all but one of the LDS measurements. After successful landing, the Orbilander spends 2 years on the surface conducting multiple LDS measurements with all five instruments on actively and passively collected plume material, as well as seismic investigations. The schedule laid out here is well-defined, but the mission also has operational and resource flexibility should additional reconnaissance be needed. As part of the design study, mission and development risks were identified and mitigation strategies proposed. Technologies key to achieving the life detection science objectives include instrumentation matured under programs like COLDTech and ICEE-2, such as aspects of the sampling system and microfluidic devices, as well as well-known techniques like high-resolution and separation-capable mass spectrometers. Autonomous onboard navigation is planned to maintain a halo orbit around Enceladus to enable passive sampling from orbit as well as reconnaissance measurements for use in site selection and landing. Terrain relative navigation is included to ensure safe landing, given that targeted areas may contain landing hazards. Continued development of radioisotope thermoelectric generator (RTG) technology and long-life batteries is essential for this long duration mission. The Enceladus Orbilander represents an optimal point in the trade space of science value versus cost, taking advantage of the extensive knowledge of Enceladus provided by Cassini, how well Enceladus lends itself to a search for life in material from its ocean, and the flexibility afforded by the innovative design developed by the APL team. By taking full advantage of Enceladus’ plumes both in orbit and on the surface, Orbilander represents a robust search for life with complementary and orthogonal biosignatures as well as contextual geophysical and geochemical measurements, determining not only whether Enceladus is inhabited (at levels up to 500,000× scarcer than in Earth’s oceans) but also why. "

Exobiology↗

NASA NTRS2007

Mapped Landmark Algorithm for Precision Landing

A report discusses a computer vision algorithm for position estimation to enable precision landing during planetary descent. The Descent Image Motion Estimation System for the Mars Exploration Rovers has been used as a starting point for creating code for precision, terrain-relative navigation during planetary landing. The algorithm is designed to be general because it handles images taken at different scales and resolutions relative to the map, and can produce mapped landmark matches for any planetary terrain of sufficient texture. These matches provide a measurement of horizontal position relative to a known landing site specified on the surface map. Multiple mapped landmarks generated per image allow for automatic detection and elimination of bad matches. Attitude and position can be generated from each image; this image-based attitude measurement can be used by the onboard navigation filter to improve the attitude estimate, which will improve the position estimates. The algorithm uses normalized correlation of grayscale images, producing precise, sub-pixel images. The algorithm has been broken into two sub-algorithms: (1) FFT Map Matching (see figure), which matches a single large template by correlation in the frequency domain, and (2) Mapped Landmark Refinement, which matches many small templates by correlation in the spatial domain. Each relies on feature selection, the homography transform, and 3D image correlation. The algorithm is implemented in C++ and is rated at Technology Readiness Level (TRL) 4.

Johnson, Andrew↗