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At least 1,027 records · Page 57

Interfacing Space Communications and Navigation Network Simulation with Distributed System Integration Laboratories (DSIL)

NASA's planned Lunar missions will involve multiple NASA centers where each participating center has a specific role and specialization. In this vision, the Constellation program (CxP)'s Distributed System Integration Laboratories (DSIL) architecture consist of multiple System Integration Labs (SILs), with simulators, emulators, testlabs and control centers interacting with each other over a broadband network to perform test and verification for mission scenarios. To support the end-to-end simulation and emulation effort of NASA' exploration initiatives, different NASA centers are interconnected to participate in distributed simulations. Currently, DSIL has interconnections among the following NASA centers: Johnson Space Center (JSC), Kennedy Space Center (KSC), Marshall Space Flight Center (MSFC) and Jet Propulsion Laboratory (JPL). Through interconnections and interactions among different NASA centers, critical resources and data can be shared, while independent simulations can be performed simultaneously at different NASA locations, to effectively utilize the simulation and emulation capabilities at each center. Furthermore, the development of DSIL can maximally leverage the existing project simulation and testing plans. In this work, we describe the specific role and development activities at JPL for Space Communications and Navigation Network (SCaN) simulator using the Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) tool to simulate communications effects among mission assets. Using MACHETE, different space network configurations among spacecrafts and ground systems of various parameter sets can be simulated. Data that is necessary for tracking, navigation, and guidance of spacecrafts such as Crew Exploration Vehicle (CEV), Crew Launch Vehicle (CLV), and Lunar Relay Satellite (LRS) and orbit calculation data are disseminated to different NASA centers and updated periodically using the High Level Architecture (HLA). In addition, the performance of DSIL under different traffic loads with different mix of data and priorities are evaluated.

Traffic Measuring and Monitoring↗

NASA Affordable Vehicle Avionics (AVA): Common Modular Avionics System for Nano-Launchers Offering Affordable Access to Space

Small satellites are becoming ever more capable of performing valuable missions for both government and commercial customers. However, currently these satellites can only be launched affordably as secondary payloads. This makes it difficult for the small satellite mission to launch when needed, to the desired orbit, and with acceptable risk. NASA Ames Research Center has developed and tested a prototype low-cost avionics package for space launch vehicles that provides complete GNC functionality in a package smaller than a tissue box with a mass less than 0.84 kg. AVA takes advantage of commercially available, low-cost, mass-produced, miniaturized sensors, filtering their more noisy inertial data with realtime GPS data. The goal of the Advanced Vehicle Avionics project is to produce and flight-verify a common suite of avionics and software that deliver affordable, capable GNC and telemetry avionics with application to multiple nano-launch vehicles at 1 the cost of current state-of-the-art avionics.

Guidance Navigation and Control↗

Linear Covariance Analysis For Proximity Operations Around Asteroid 2008 EV5

The NASA initiative to collect an asteroid, the Asteroid Robotic Redirect Mission (ARRM), is currently investigating the option of retrieving a boulder from an asteroid, demonstrating planetary defense with an enhanced gravity tractor technique, and returning it to a lunar orbit. Techniques for accomplishing this are being investigated by the Satellite Servicing Capabilities Office (SSCO) at NASA GSFC in collaboration with JPL, NASA JSC, LaRC, and Draper Laboratory, Inc. Two critical phases of the mission are the descent to the boulder and the Enhanced Gravity Tractor demonstration. A linear covariance analysis is done for these phases to assess the feasibility of these concepts with the proposed design of the sensor and actuator suite of the Asteroid Redirect Vehicle (ARV). The sensor suite for this analysis includes a wide field of view camera, LiDAR, and an IMU. The proposed asteroid of interest is currently the C-type asteroid 2008 EV5, a carbonaceous chondrite that is of high interest to the scientific community. This paper presents an overview of the linear covariance analysis techniques and simulation tool, provides sensor and actuator models, and addresses the feasibility of descending to the surface of the asteroid within allocated requirements as well as the possibility of maintaining a halo orbit to demonstrate the Enhanced Gravity Tractor technique.

Navigation↗

Relative Terrain Imaging Navigation (RETINA) Tool for the Asteroid Redirect Robotic Mission (ARRM)

As a part of the NASA initiative to collect a boulder off of an asteroid and return it to Lunar orbit, the Satellite Servicing Capabilities Office (SSCO) and NASA GSFC are developing an on-board relative terrain imaging navigation algorithm for the Asteroid Redirect Robotic Mission (ARRM). After performing several flybys and dry runs to verify and refine the shape, spin, and gravity models and obtain centimeter level imagery, the spacecraft will descend to the surface of the asteroid to capture a boulder and return it to Lunar Orbit. The algorithm implements Stereophotoclinometry methods to register landmarks with images taken onboard the spacecraft, and use these measurements to estimate the position and orientation of the spacecraft with respect to the asteroid. This paper will present an overview of the ARRM GN&C system and concept of operations as well as a description of the algorithm and its implementation. These techniques will be demonstrated for the descent to the surface of the proposed asteroid of interest, 2008 EV5, and preliminary results will be shown.

Navigation↗

Performance Characterization of a Landmark Measurement System for ARRM Terrain Relative Navigation

This paper describes the landmark measurement system being developed for terrain relative navigation on NASAs Asteroid Redirect Robotic Mission (ARRM),and the results of a performance characterization study given realistic navigational and model errors. The system is called Retina, and is derived from the stereophotoclinometry methods widely used on other small-body missions. The system is simulated using synthetic imagery of the asteroid surface and discussion is given on various algorithmic design choices. Unlike other missions, ARRMs Retina is the first planned autonomous use of these methods during the close-proximity and descent phase of the mission.

Navigation↗

Analyzing JAVAD TR-G2 GPS Receiver's Sensitivities to SLS Trajectory

Automated guidance and navigation systems are an integral part to successful space missions. Previous researchers created Python tools to receive and parse data from a JAVAD TR-G2 space-capable GPS receiver. I improved the tool by customizing the output for plotting and comparing several simulations. I analyzed position errors, data loss, and signal loss by comparing simulated receiver data from an IFEN GPS simulator to ‘truth data’ from a proposed trajectory. By adjusting the trajectory simulation’s gain, attitude, and start time, NASA can assess the best time to launch the SLS, where to position the antennas on the Block 1-B, and which filter to use. Some additional testing has begun with the Novatel SpaceQuestGPS receiver as well as a GNSS SDR receiver.

Schuler, Tristan↗

Using Systems Engineering to Develop an Integrated Crew Health and Performance System to Mitigate Risk for Human Exploration Missions

New space exploration missions are currently being designed to take humanity beyond low Earth orbit (LEO) to cis-lunar space, the lunar surface, and eventually to Mars. These missions carry increased risks due to a number of factors, including distance from Earth, exposure to deep space hazards, reduced capacity and ability to resupply and evacuate, and increased communication delays. As distance from Earth grows and mission length increases, a growing proportion of mission risk can be attributed to the “human system.” Almost twenty years ago, the Institute of Medicine in the United States recommended the early and complete integration of the human system into the spacecraft and mission design process to mitigate this increased risk inherent in exploration missions. Exploration missions will require increasing levels of crew self-sufficiency that will challenge the current operational paradigms established in LEO. Enabling progressive Earth independence requires management of the increasingly complex interactions among spacecraft systems and integration of all the data and functions that affect human health and performance into one coordinated system –the Crew Health and Performance (CHP) system. This system is a critical spacecraft system that is analogous to other systems such as propulsion, guidance and navigation, or avionics. Design and integration of the CHP system requires the evidence-based merger of typically disparate disciplines such as medicine, human factors, and life support system design, using systems engineering (SE) practices. SE provides traceability of spacecraft requirements and enables reliable and repeatable trade space analysis of the many competing options for hardware and software to be included in the mission architecture. The approach described here enables spacecraft and mission designers to align the scope of a CHP system with mission specific requirements, decrease risk to the crew, and increase the probability of mission success.

Kerry McGuire↗

Small Inertial Measurement Units- Sources of Error and Limitations on Accuracy

Inertial measurement units (IMUs) with very low mass and power can be manufactured using micromachined accelerometers and gyroscopes. Six degree of freedom packages which require a few watts of power and have less than a kg of mass are available commercially, greatly expanding the potential applications of IMUs in guidance and navigation. Recent advances in small sensor design and fabrication have pushed the performance limits of these small devices. However, the limitations on the precision of small IMUs are not entirely due to the performance of the individual sensors.

Hoenk, Michael E.↗

Using Systems Engineering to Develop an Integrated Crew Health and Performance System to Mitigate Risk for Human Exploration Missions

New space exploration missions are currently being designed to take humanity beyond Low EarthOrbit (LEO) to cis-lunar space, the lunar surface, and eventually to Mars. These missions carryincreased risks due to a number of factors, including distance from Earth, exposure to deep spacehazards, reduced capacity and ability to resupply and evacuate, and increased communication delays.As distance from Earth grows and mission length increases, a growing proportion of overall missionrisk can be attributed to the “human system.” Almost twenty years ago, the Institute of Medicine in theUnited States recommended the early and complete integration of the human system into thespacecraft and mission design process to mitigate this increased risk inherent in exploration missions.Exploration missions will require increasing levels of crew self-sufficiency that will challenge thecurrent operational paradigms established in LEO. Enabling progressive Earth independence requiresmanagement of the increasingly complex interactions among spacecraft systems and integration of allthe data and functions that affect human health and performance into one coordinated system – theCrew Health and Performance (CHP) system. This system is a critical spacecraft system that isanalogous to other systems such as propulsion, guidance and navigation, or avionics. Design andintegration of the CHP system requires the evidence-based merger of typically disparate disciplinessuch as medicine, human factors, and physiological support system design, using systems engineering(SE) practices. The approach described here enables spacecraft and mission designers to align thescope of a CHP system with mission specific requirements, decrease risk to the crew, and increase theprobability of mission success.

Kerry Mcguire↗

Spacecraft Line-Of-Sight Jitter Mitigation and Management Lessons Learned and Engineering Best Practices

Predicting, managing, controlling, and testing spacecraft line-of-sight (LoS) jitter caused by micro-vibrations due to onboard internal disturbance sources is a formidable multidisciplinary engineering task. It is especially challenging for those missions hosting high-performance, vibration-sensitive optical sensor payloads with stringent pointing stability requirements. Both NASA and ESA are planning technically aggressive spaceflight missions that include ultra-high-performance optical payloads with delicate, highly vibration-sensitive scientific and observational instruments. The GN&C community of practice will need to leverage and build upon their collective experiences and lessons learned to better address future micro-vibration challenges. To identify lessons learned and best engineering practices the NASA Engineering & Safety Center (NESC) sponsored a two-day Spacecraft LoS Jitter Workshop in late 2019. The workshop’s goal was to provide a multidisciplinary forum to elicit deeper understanding of the issues related to solving the spacecraft LoS jitter/micro-vibration problem. A primary objective was to identify and share best practices, rules of thumb, and options for jitter-related activities. Representatives from NASA, JPL, ESA, along with NASA’s industrial partners, independent consultant subject matter experts, and members of academia participated in the workshop. This paper will describe the motivation for the NASA Spacecraft LoS Jitter Workshop and summarize the identified findings, observations, and recommendations.

Lessons Learned;↗

NESC GN&C TDT Workshop on 2D Image Motion Optical Transfer Functions, Pointing Performance Analysis, and Requirements

What You Will Learn: The focus is on payload imaging performance due to pointing motion. Some historical background on pointing performance analysis is given. The Optical Transfer Function (OTF) and Modulation Transfer Function (MTF) are defined. The imaging performance due to pointing motion is measured by image motion optical transfer functions (IM OTF). IM OTFs are defined for displacement, smear, and jitter motions, which are all rigorously defined. Deterministic and Statistical IM OTFs are briefly derived and graphically illustrated and compared. The IM OTFs are parameterized by pointing error metrics(PEM), which are means and covariances of displacement, smear, and jitter. Emphasis is on procedures and algorithms to evaluate the image motion optical transfer functions and pointing error metrics. Three procedures are covered, which depend on whether the pointing error data is from time-domain simulation, frequency-domain analysis, or stochastic modeling. A method to evaluate the relative contribution of disturbance sources and to identify the most significant contributors is presented. The presentation includes pertinent discussion of flexible structures and control-structure interaction. No single book can adequately cover this subject, so a book is not required for the course. A list of selected articles, reports, documents, and books is provided for reference and further study. Mathis kept to the minimum necessary to convey principles; lengthy derivations are left to the reference material. Graphics are used to illustrate concepts. As with any such learning endeavor, the knowledge gained will be retained and strengthened through actual practice.c©2019–2021 Mark E. Pittelkau— 5

NASA Engineering and Safety Center (NESC)↗

NESC GN&C TDT Workshop on 2D Image Motion Optical Transfer Functions, Pointing Performance Analysis, and Requirements

This course was prepared by the author in support of the NASA GN&C Technical Discipline Team (TDT). The purpose of this two-day course is to inform practicing GN&C engineers, and other system and subsystem engineers, including payload engineers and mission analysts, of methodologies to analyze the pointing performance of spacecraft and to write unambiguous pointing requirements that are relevant to optical payload performance. It is hoped that the seminar will contribute to a best-practices manual and contribute to accepted and uniform means of requirements definition, validation, and verification. The course material is designed to address the needs of not only practicing GN&C engineers, but also system and subsystem engineers of other disciplines, payload engineers, mission analysts, and even astronomers who need to understand how they interface to a GN&C subsystem. Much revision is the direct result of active student participation during the presentations and from feedback obtained through course evaluation forms.

2D Image↗

A Generalized Guidance Approach to In-Space Solid-Propellant Vehicle Maneuvers

Exploration-class vehicles that require fully autonomous ascent and descent must employ robust, explicit path-adaptive guidance algorithms that can operate in a wide range of physical environments. Vehicle designs that employ solid-propellant rocket motors (SRMs) for maneuvers are attractive from a systems engineering perspective because of their simplicity and reliability, but may cause complications for both mission designers and GNC engineers when dealing with total impulse uncertainty, as well as proper energy management of a motor with an uncontrolled cutoff time. This paper presents a simplified guidance algorithm, named Simple Cross-Product Steering (SxS), that was derived during early studies of NASA’s Mars Sample Return mission’s Mars Ascent Vehicle. The algorithm takes roots in a flight-proven guidance algorithm commonly referred to as Cross-Product Steering. SxS has been shown to provide sufficient guidance accuracy for in-space SRM burns in a simulated Martian environment, and preliminary studies have been conducted to test the algorithm in a solid-propellant lunar braking scenario. A method for predicting proper motor ignition time during execution of the Cross-Product Steering algorithm is the primary contribution of this paper. Mechanization notes are also provided that were realized in early phases of MAV. Results are shown for an example ascent vehicle in a simulated Mars environment.

GNC↗

Attitude Profile Reference for the Earth Orbit Raising Phase of NASA Gateway’s Co-Manifested Vehicle

As part of NASAs lunar exploration Artemis program, the agency is designing a Gateway to orbit8near the moon and provide long term support of a sustained lunar presence at the moon’s south pole.9The first element launched for the Gateway is the Co-Manifested Vehicle (CMV), comprised of the10Power and Propulsion Element (PPE) and Habitation and Lunar Outpost (HALO). The PPE Mission11Design team of McGuire & et. al (2021) has developed a Design Reference Mission (DRM) trajectory12for CMV’s Earth Orbit Raising (EOR) mission phase, which provides the vehicle’s 3 degrees of freedom13(DoF) trajectory information during the approximately yearlong spiral out from low Earth orbit and14into the lunar near-rectilinear halo orbit (NRHO). In tandem, the PPE GN&C team is developing a15high-fidelity and fine temporal resolution 6DoF model of the CMV spacecrafts GN&C performance16for delivery to the Gateway team; this work acts to bridge the gap between Mission Designs 3DoF17reference and detailed GN&Cs attitude simulation.

Guidance Navigation and Control↗

Investigating Solar Radiation Pressure Modeling for Operations in Near Rectilinear Halo Orbit

NASA’s Gateway program will build a crew-tended station in an Earth-Moon Near Rectilinear Halo Orbit (NRHO). Deep space operations differ considerably from Low Earth Orbit (LEO) operations in the environmental modeling, orbit geometry, and propagation timespans in operations. The cislunar environment, as opposed to the LEO environment, lacks atmospheric drag and is simultaneously affected by the gravity of both the Earth and the Moon, and solar radiation pressure (SRP) has a significant effect. This paper investigates the impacts of various SRP models on prediction accuracy, attitude control accuracy, orbit determination performance, and computational burden.

Guidance↗