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NASA NTRS2023

Extended Kalman Filter Performance on the Artemis-1 Mission

The Artemis Program is NASA’s campaign to explore the Moon and beyond. Artemis-1, the uncrewed exoLEO test flight of the Orion spacecraft, was completed in 2022. There were four navigation Extended Kalman Filters (EKFs) that are part of the Orion navigation system. The Atmospheric Extended Kalman Filter (ATMEKF) estimates the vehicle position, velocity, and attitude (referred to as the vehicle state) during the ascent and entry phases of flight. Once Orion is outside of Earths atmosphere, the Earth Orbit Extended Kalman Filter (EOEKF) and CisLunar Extended Kalman Filter (CLEKF) estimate the translational states, depending on the phase of flight, while the Attitude Extended Kalman Filter (ATTEKF) estimates the rotational state of the vehicle. The Kalman filters propagate the vehicle state forward in time using a combination of dynamics models and the output data from the Inertial Measurement Unit (IMU). The filters update the vehicle states and associated uncertainties, in the form of the covariance matrix, using pseudorange measurements from GPS (in ATMEKF/EOEKF), optical navigation measurements of the Earth or Moon (in CLEKF), and star tracker measurements (in ATTEKF). Simultaneously, the Kalman filters estimate error sources in the sensors, which are included in the state vectors as Exponentially Correlated Random Variables (ECRVs). This paper will summarize the performance of these filters during the Artemis-1 mission.

Artemis-1↗
NASA NTRSDate not supplied

Toward A Method for Scaling Human Body Models in an IMU-Based Workflow

- Scaled biomechanical models can more accurately inform crew health decisions when tailored to the wide range of astronaut sizes. One component to improve scaling of existing models to better represent each unique astronaut’s size is the individual length scaling of limbs. Traditionally, limb lengths are determined by motion capture or manual measurement. - A new method is herein proposed for length scaling which can be done by measuring linear and angular accelerations at a desired point during isolated motion around a point of rotation, then calculating the distance between the desired point and point of rotation. - When an Inertial Measurement Unit (IMU) device is placed at the distal point of a limb, the isolated motion is about that limb’s proximal joint. This method of scaling limb segments can be used for any limb that has an easily defined proximal joint for the limb to rotate around including hands, arms, legs, feet. - Calculated limb lengths are then used to scale models to each unique astronaut’s size, thereby improving the applicability of the model. - This method was investigated as a possible away to obtain scaling information in data collections where IMUs are worn, but optical motion capture may not always be available, such as inside spacesuits or during crew exercise on the International Space Station.

E. K. Marecki↗
NASA NTRSDate not supplied

Artemis I Orion IMU Flight Performance

The Orion flight software’s parity algorithm runs onboard to verify all three OIMUs (Orion Inertial Measurement Units) are sensing relatively uniform rate and acceleration and to quickly identify any unit which is in significant disagreement with the other two units. During the Artemis-I Wet Dress Rehearsal tests and Launch Countdowns, one of the three OIMUs regularly reported an anomalous parity signature for a brief period of time during sensor warm up. This paper will review this anomalous performance on the pad and review flight data with the intent to supplement the findings of the initial root cause investigation. Outside of this start up behavior, initial investigation into Artemis I flight data did not reveal any behavior of the OIMUs outside of preflight expectations. Flight data from any significant parity events and relevant IMU calibrations will be presented. A brief discussion of impacts to future Artemis mission operations strategy will be provided.

Robert Earl↗
NASA NTRS2021

Mars 2020 Perseverance Entry Controller Design and Flight Reconstruction

On February 18th, 2021, NASA landed Perseverance on the Jezero crater (on Mars). An entry Guidance, Navigation, and Control (GNC) system delivered the vehicle to the desired landing ellipse. The navigation filter propagated position and attitude states initialized from cruise using Inertial Measurement Unit (IMU) measurements. The entry guidance modulated the lift vector through bank commands to reach the parachute deploy conditions. The entry controller commanded the propulsive Reaction Control System (RCS) to track the bank commands while doing rate damping on angle-of-attack and sideslip. This paper describes the design and the as-flown performance of the entry controller.

Way, David W.↗
NASA NTRS2021

The Mars 2020 Perseverance Navigation Filter

The Mars 2020 (M2020) Entry Descent and Landing (EDL) system delivered a rover named “Perseverance” at Jezero crater (Mars) on February 18th, 2021. M2020 EDL used a Guidance Navigation and Control (GN&C) system to achieve its landing target objectives. The navigation filter (NavFilter) integrated Descent Inertial Measurement Unit (DIMU) measurements to estimate position and attitude. The NavFilter also used the Terminal Descent Sensor (TDS) to es-timate surface-relative position and velocity corrections. The NavFilter provided all of the dynamic state information to the entry controller, entry guidance, Lander Vision System (LVS) and powered descent guidance and control algo-rithms. The NavFilter for Perseverance is based on Curiosity’s NavFilter with a couple of modifications.

Casoliva, Jordi↗
NASA NTRS2022

Performance Analysis of Terrain Relative Navigation Using Blue Origin New Shepard Suborbital Flight Telemetry

As part of a NASA Tipping Point Partnership with Blue Origin to mature precision lunar landing technologies, two test flights of the Blue Origin New Shepard vehicle carrying a NASA-developed sensor suite were conducted on 10/13/2020 and 08/26/2021 at the West Texas Launch Site (LS-1). Part of the acquired datasets, comprising data from an inertial measurement unit and a downward facing camera, was postprocessed through a JPL-developed prototype Visual Odometry and Map Relative Localization software (TRNVOSIM), and compared against ground truth acquired by the host vehicle navigation system. In this paper, we provide a description of the algorithms, the test setup, and the processed results.

Pedrotty, Samuel M.↗
NASA NTRS2022

Vision-based Velocimetry over Unknown Terrain with a Low-Noise IMU

This paper presents a novel approach to terrain-relative navigation with a visual camera and Inertial Measurement Unit (IMU). The proposed algorithm uses an Extended Kalman Filter (EKF) to combine an IMU propagated state estimate with batch correction estimates computed over a sliding window of measurements. The batch correction algorithm follows the Maximum Likelihood Estimation (MLE) approach used in other Bundle Adjustment systems. Unlike other systems, the proposed system parameterizes the state over the entire window in terms of the state at a single epoch. By ignoring IMU error over the window duration, we obtain a state epoch MLE that jointly estimates the epoch state and terrain parameters with drastically reduced computationally cost. This paper presents the general architecture which can be adapted for various state parameterizations and measurement inputs. For space applications with high-accuracy IMUs, the reduction in computational cost comes with only a modest increase in estimation errors. The increase in error is quantified via a linear covariance analysis presented in this paper. Furthermore, we present simulation results which show the applicability of this algorithm to planetary landing problems.

San Martin, A. Miguel↗
NASA NTRS2021

Analysis of Mars 2020 Perseverance Entry, Descent, and Landing Attitude Initialization Performance

The Mars 2020 Perseverance rover successfully landed at Jezero Crater on February 18, 2021. To perform this feat, the entry, descent, and landing navigation filter must be initialized with an estimate of the spacecraft state, which includes attitude from the cruise attitude control subsystem. Accuracy of this initial attitude estimate has an impact on important metrics such as touchdown velocity. This paper presents a post-landing reconstruction of the attitude initialization error budget, showing that the requirement of 0.15 deg ($3\sigma$, per axis) was met. Each error source is described and analyzed, including flight telemetry where possible. Analysis of the error budget shows that it is driven by systematic sun sensor errors, star-scanner-to-sun-sensor alignment stability, and inertial-measurement-unit-to-sun-sensor alignment stability. Finally, a contingency plan to initialize the navigation filter in the event of a star scanner failure is presented. While this plan was not needed in flight, results indicate that the attitude initialization requirement could have still been met in this off-nominal scenario.

Lo, Kevin D.↗
NASA NTRS2022

Reconstructed Performance of the Mars InSight Lander’s Supersonic Parachute & Comparison with the Phoenix Lander

On November 26th, 2018 the Mars InSight landersuccessfully touched down at Elysium Planitia. InSight’s Entry,Descent, and Landing sequence included an 11.8-m supersonicallydeployed Disk-Gap-Band parachute that was a largelybuild-to-print version of the parachute used to successfully landthe Phoenix lander a decade earlier. This paper describes thereconstructed performance of InSight’s supersonic parachuteat Mars, highlighting the differences and similarities with theperformance of Phoenix’s parachute. Measurements from theonboard inertial measurement unit along with pre-launch measurementsof the parachute system and spacecraft, assumptionsabout the vehicle’s aerodynamics, and models for the Martianatmosphere were used to reconstruct the spacecraft’s trajectoryand the parachute system’s performance. The reconstruction resultswere compared against pre-flight predictions. Reconstructionof the InSight trajectory leading up to parachute deploymentshowed that the vehicle trimmed in a lift-down orientationduring entry and thus experienced greater deceleration thanexpected by most pre-flight simulations. This led to parachutedeployment conditions that diverged from the nominal preflightpredictions. The parachute was mortar-deployed at aMach number of approximately 1.5, below the nominal preflightexpectation of 1.66. The approximate dynamic pressureat mortar fire was between 518 Pa and 546 Pa, which agreedwell with pre-flight expectations. The mortar system performednominally, and the system’s deployment (0.755 s) and inflation(1.1 s) times were in line with pre-flight modeling. The peakinflation load was 45 kN, well below the parachute’s 67 kNdesign limit load. Following deployment of the parachute,the vehicle’s rotational rates and the dynamics of the systemwere in excellent agreement with pre-flight expectations. Theperformance of the InSight parachute system was also foundto agree well with that of the Phoenix parachute system, asexpected given the similarities between the two systems.

Karlgaard, Chris↗
NASA NTRS2022

Mars 2020 Lander Vision System Flight Performance 1

The Mars 2020 Entry Descent and Landing (EDL) system delivered the Perseverance rover to the surface of Mars on February 18th, 2021. A large fraction of the Jezero Crater landing site was covered with landing hazards including cliffs, inescapable dune fields and rocks. These hazards were identified or inferred using orbital imagery before launch so that they could be avoided using Terrain Relative Navigation (TRN) which was composed of two parts: the Lander Vision System (LVS) and Safe Target Selection (STS). During EDL, the LVS successfully estimated map relative position by fusing landmarks matched between descent imagery and a map of the landing site with Inertial Measurement Unit (IMU) data. This position estimate was used by STS to identify the safest target for landing that was also reachable given fuel and other constraints. The EDL system then used the powered descent phase to retarget to this location and land safely. The overall error between the targeted location and actual landing location was 5m which was an order of magnitude less than the 60m touchdown error requirement. This paper will describe the final tests of the LVS before launch, the checkout of the LVS during operations and the LVS performance during EDL.

Zheng, Jason↗
NASA NTRS2022

Automating Surface Attitude Positioning and Pointing Operations for Mars 2020

The Surface Attitude Positioning and Pointing (SAPP) subsystem of the Mars Perseverance rover keeps track of the rover’s position and attitude on the surface of Mars. The SAPP Downlink Engineering Operations team members receive data from the rover on a daily basis. They must interpret the data to make sure the rover is staying safe and to support uplink planning. The SAPP team keeps track of the error growth in the rover’s attitude estimate due to noise in the Rover Inertial Measurement Unit’s (RIMU) gyroscopes used to propagate that attitude estimate whenever the rover is moving. Whenever this error grows to a particular threshold, SAPP is responsible for updating the onboard attitude knowledge using the RIMU’s accelerometers to estimate rover roll and pitch and sun imaging to estimate rover yaw, thereby reducing this attitude estimation error. Accurate attitude estimation is required so that the rover can successfully point its High Gain Antenna (HGA) to receive information from Earth and as a backup to the Mars orbiters used for sending data from the rover to Earth, point instruments on its Remote Sensing Mast (RSM), and support safe movement and placement of instruments by the rover’s ARM relative to the Martian surface. The Mars 2020 Engineering Operations team has been working to increase the operational efficiency of the mission and eventually move to a five-hour timeline for daily operations. In pursuit of this goal, the SAPP Engineering Operations team has automated their downlink process by developing a centralized Jupyter notebook to analyze the data received daily from the rover. The SAPP downlink Jupyter notebook automatically collects the data relevant to the SAPP subsystem and visualizes this information in plots and tables that can be easily read by downlink operators to aid them in assessing the status of the subsystem. Various Application Programming Interfaces (APIs) have been incorporated into the downlink daily notebook to automate the collection and posting of data, such as gathering and posting data products to the cloud. The SAPP team has also developed a SAPP downlink software library that includes functions to aid the notebook in processing data. In addition to assessing the SAPP subsystem on a daily basis, operators need to assess the long-term trending behavior of the subsystem over time. An automated trending process has been developed to collect information from the daily notebooks in order to plot and analyze that data in a centralized place. These daily and trending processes have expedited the SAPP downlink assessment and laid the groundwork to completely automate the SAPP downlink process so that SAPP operators are unnecessary unless something unexpected occurs. This paper will provide an overview of the functions that the SAPP subsystem carries out on a daily basis, and will then dive into the automations that have been developed for daily and trending downlink assessment. An assessment of the downlink efficiency will be provided, along with a summary of lessons learned and work to go. Finally, the authors will discuss how these types of automated spacecraft health assessments could be more broadly used within mission operations.

Zarifian, Anais↗
NASA NTRSDate not supplied

Overview and Performance of the LOFTID Instrumentation Suite

NASA’s Hypersonic Inflatable Aerodynamic Decelerator (HIAD) is an enabling technology that facilitates atmospheric entry of heavy payloads to planets such as Earth and Mars using a deployable aeroshell. The deployable nature of the HIAD technology allows it to overcome the size constraints imposed on current rigid aeroshell entry systems. This enables use of larger aeroshells resulting in increased entry system performance (e.g. higher payload mass and/or volume, higher landing altitude at Mars). On November 10th, 2022 the Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) was launched out of Vandenberg Air Force Base as a secondary payload on an Atlas V rocket. After the primary payload was delivered to its orbit, the LOFTID reentry vehicle was inflated, positioned, and then separated to reenter Earth’s atmosphere at a velocity of 8.1km/s, ultimately splashing down safely in the Pacific Ocean. The flight successfully demonstrated a 6m diameter, 70-deg sphere-cone HIAD on a high-energy orbital reentry. This demonstration has provided invaluable fight data essential to characterize the vehicle performance and support the ongoing effort to further scale the HIAD technology to vehicles of 10m in diameter or greater. Aeroshells of this scale are applicable to near-term commercial applications and future NASA robotic and human exploration missions. LOFTID incorporated an extensive instrumentation suite totaling over 150 science measurements. This included thermocouples, total heat flux sensors, and a radiometer to characterize the aeroheating environment and aeroshell thermal response. An Inertial Measurement Unit (IMU), Global Positioning System (GPS), and flush air data system was included to allow post-flight reconstruction of the vehicle trajectory including a decoupling of the aerodynamics from the atmospheric density. Loadcells were used to measure HIAD structural response during entry, and cameras (both visual-spectrum and infrared) were mounted on the aft segment looking at the aeroshell to monitor structural deflection and surface temperature distribution. Finally, a single up-look camera was included which has provided a surprising amount of science potential from the spectacular footage. In addition to the primary instrumentation suite, a new Fiber Optic Sensing System (FOSS) was used to provide global temperature distributions as a technology demonstration. The system provided over 200 thermal measurements creating a thermal map for the backside of the nose Flexible Thermal Protection System. Another pair of FOSS cables were run along the rigid center structure and measured the temperature response to the vehicle wake environment. The LOFTID instrumentation suite leveraged Agency-wide expertise, with hardware development occurring at Ames Research Center, Langley Research Center, Marshall Space Flight Center, and Armstrong Flight Research Center. This presentation will discuss the instrumentation selected for LOFTID to capture the HIAD performance during the high-energy orbital reentry flight test, provide examples of data products, and snippets of the spectacular reentry video.

G T Swanson↗
NASA NTRSDate not supplied

Overview and Performance of the LOFTID Instrumentation Suite

NASA’s Hypersonic Inflatable Aerodynamic Decelerator (HIAD) is an enabling technology that facilitates atmospheric entry of heavy payloads to planets such as Earth and Mars using a deployable aeroshell. The deployable nature of the HIAD technology allows it to overcome the size constraints imposed on current rigid aeroshell entry systems. This enables use of larger aeroshells resulting in increased entry system performance (e.g. higher payload mass and/or volume, higher landing altitude at Mars). On November 10th, 2022 the Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) was launched out of Vandenberg Air Force Base as a secondary payload on an Atlas V rocket. After the primary payload was delivered to its orbit, the LOFTID reentry vehicle was inflated, positioned, and then separated to reenter Earth’s atmosphere at a velocity of 8.1km/s, ultimately splashing down safely in the Pacific Ocean. The flight successfully demonstrated a 6m diameter, 70-deg sphere-cone HIAD on a high-energy orbital reentry. This demonstration has provided invaluable fight data essential to characterize the vehicle performance and support the ongoing effort to further scale the HIAD technology to vehicles of 10m in diameter or greater. Aeroshells of this scale are applicable to near-term commercial applications and future NASA robotic and human exploration missions. LOFTID incorporated an extensive instrumentation suite totaling over 150 science measurements. This included thermocouples, total heat flux sensors, and a radiometer to characterize the aeroheating environment and aeroshell thermal response. An Inertial Measurement Unit (IMU), Global Positioning System (GPS), and flush air data system was included to allow post-flight reconstruction of the vehicle trajectory including a decoupling of the aerodynamics from the atmospheric density. Loadcells were used to measure HIAD structural response during entry, and cameras (both visual-spectrum and infrared) were mounted on the aft segment looking at the aeroshell to monitor structural deflection and surface temperature distribution. Finally, a single up-look camera was included which has provided a surprising amount of science potential from the spectacular footage. In addition to the primary instrumentation suite, a new Fiber Optic Sensing System (FOSS) was used to provide global temperature distributions as a technology demonstration. The system provided over 200 thermal measurements creating a thermal map for the backside of the nose Flexible Thermal Protection System. Another pair of FOSS cables were run along the rigid center structure and measured the temperature response to the vehicle wake environment. The LOFTID instrumentation suite leveraged Agency-wide expertise, with hardware development occurring at Ames Research Center, Langley Research Center, Marshall Space Flight Center, and Armstrong Flight Research Center. This paper will discuss the instrumentation selected for LOFTID, a summary of sensor in-flight performance, and will provide examples of data products from the post-flight analysis effort.

Gregory T Swanson↗
NASA NTRS2020

Preliminary Design, Testing, and Performance of the LOFTID Navigation System

The Low Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) involves the first orbital test of an inflatable decelerator. This test involves the LOFTID re-entry vehicle using an inflatable decelerator to re-enter the atmosphere after flying to orbit as a secondary payload. Due to system constraints, including spin stabilization, unknown time of day, a limited space available for antennas, and a heat shield which blocks magnetic fields, the navigation system includes only an inertial measurement unit and a single GPS receiver. As the vehicle is turned off for the first part of the mission and will not receive commands or data from the ground, the navigation system will not have accurate initialization, and will in-stead rely on pre-flight estimates or first measurement estimation. This could result in significant unknown error in the initial state, resulting in needing to initialize the state on-orbit and requires using the single GPS antenna for attitude updates. These design considerations led to using an Extended Kalman filter, modified to perform with these design constraints. A streamlined testing approach, including tests with flight-like rotations, is being used to limit the time and resources needed to test the navigation system while still fully testing the performance and robustness of the navigation system. This testing approach follows the NASA test-as-you-fly principle and allows for early detection of errors and changes that are needed in the software. This results in a navigation system that, even within the design constraints of the mission architecture, will provide the performance and robustness needed of the mission.

Joel Amert↗
NASA NTRSDate not supplied

Leveraging VIPER Geotechnical and Mobility Insights for Endurance Rover and Traverse Development

A new generation of lunar surface rover exploration is rapidly approaching. This is evidenced by the rise of commercially developed rovers from private companies (e.g., Lunar Outpost’s MAPP) and government agencies, like NASA’s Volatiles Investigating Polar Exploration Rover (VIPER), the Lunar Terrain Vehicle (LTV), and the Endurance/Intrepid rover concepts, and the INSPIRE mission concept. The drive distance requirements for off-world vehicles are also rapidly increasing. For example, LTV driving requirements dictate a 20 km range on a single battery charge, with an overall lifetime requirement of 13,000 km over a minimum 10-year service life. Similarly, NASA's Endurance-A mission concept requires a 2000 km vehicle traverse distance, which is nearly 50 times further than the USSR's Lunokhod 2, the longest lunar rover mission to date. Previous planetary surface missions on the Moon and Mars have revealed harsh mobility conditions: aggressive rocky terrains on Mars severely damaged the Curiosity rover’s wheels, soft lunar regolith caused the Lunokhod 2 rover to sink and NASA’s Apollo 15 LRV (Lunar Roving Vehicle) spun out due to poor traction, which required manual correction. This demonstrates that mobility challenges like wheel degradation and soft soil driving performance must be accounted for in a mission’s design phase to meet increasingly aggressive mission durations and mobility goals. The success of these long duration missions requires highly reliable and durable mobility platforms in conjunction with a more developed understanding of the geotechnical properties of the lunar surface. The VIPER mission is uniquely posed to inform future missions about mobility performance, wheel durability, and lunar surface soil mechanics of sunlit and shadowed regions through use of data streams that already exist for other mission purposes. VIPER’s mission to the lunar south pole will provide a new perspective into off-world mobility challenges including traversal into permanently shadowed regions. Mobility data from VIPER’s mission will represent a first glimpse into the surface mobility challenges of the lunar South Pole. Utilization of VIPER’s existing capabilities including cameras, inertial measurement unit (IMU) data, motor currents/torque, drill data, and the rover’s suspension state and kinematics provide the opportunity to determine potentially useful information for future rover and traverse designs, as well as on-Earth testing practices. Data products collected during VIPER’s mission could inform design considerations for the Endurance rover much earlier than NASA’s standard “lessons learned” approach as VIPER has a highly tactical mission operations structure. This work outlines the specific links between possible data products from the VIPER mission and their potential impact on the Endurance/Intrepid mission concepts in their early design phases. From VIPER, we will also gain insights for future development of onboard mobility software as VIPER is a way-point driven rover which requires more constant human operation on Earth than some other rover missions (non-lunar surface). Primary VIPER data products and insights of interest include wheel sinkage, wheel slip, wheel degradation, surface soil shear strength, and terrain slope estimation. VIPER data products will be made available via the Planetary Data System’s Geosciences and Cartography and Imaging Sciences nodes, conforming to the PDS4 standard.

mobility↗
NASA NTRSDate not supplied

Overview and Performance of the LOFTID Instrumentation Suite

NASA’s Hypersonic Inflatable Aerodynamic Decelerator (HIAD) is an enabling technology that facilitates atmospheric entry of heavy payloads to planets such as Earth and Mars using a deployable aeroshell. The deployable nature of the HIAD technology allows it to overcome the size constraints imposed on current rigid aeroshell entry systems. This enables use of larger aeroshells resulting in increased entry system performance (e.g. higher payload mass and/or volume, higher landing altitude at Mars). On November 10th, 2022 the Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) was launched out of Vandenberg Air Force Base as a secondary payload on an Atlas V rocket. After the primary payload was delivered to its orbit, the LOFTID reentry vehicle was inflated, positioned, and then separated to reenter Earth’s atmosphere at a velocity of 8.1km/s, ultimately splashing down safely in the Pacific Ocean. The flight successfully demonstrated a 6m diameter, 70-deg sphere-cone HIAD on a high-energy orbital reentry. This demonstration has provided invaluable fight data essential to characterize the vehicle performance and support the ongoing effort to further scale the HIAD technology to vehicles of 10m in diameter or greater. Aeroshells of this scale are applicable to near-term commercial applications and future NASA robotic and human exploration missions. LOFTID incorporated an extensive instrumentation suite totaling over 150 science measurements. This included thermocouples, total heat flux sensors, and a radiometer to characterize the aeroheating environment and aeroshell thermal response. An Inertial Measurement Unit (IMU), Global Positioning System (GPS), and flush air data system was included to allow post-flight reconstruction of the vehicle trajectory including a decoupling of the aerodynamics from the atmospheric density. Loadcells were used to measure HIAD structural response during entry, and cameras (both visual-spectrum and infrared) were mounted on the aft segment looking at the aeroshell to monitor structural deflection and surface temperature distribution. Finally, a single up-look camera was included which has provided a surprising amount of science potential from the spectacular footage. In addition to the primary instrumentation suite, a new Fiber Optic Sensing System (FOSS) was used to provide global temperature distributions as a technology demonstration. The system provided over 200 thermal measurements creating a thermal map for the backside of the nose Flexible Thermal Protection System. Another pair of FOSS cables were run along the rigid center structure and measured the temperature response to the vehicle wake environment. The LOFTID instrumentation suite leveraged Agency-wide expertise, with hardware development occurring at Ames Research Center, Langley Research Center, Marshall Space Flight Center, and Armstrong Flight Research Center. This paper will discuss the instrumentation selected for LOFTID, a summary of sensor in-flight performance, and will provide examples of data products from the post-flight analysis effort.

Greg Swanson↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

Kinematic Sensors Evaluation for Spaceflight Exercise Data Collections

INTRODUCTION: On the International Space Station (ISS), exercise feedback from astronauts is very important to diagnose and mitigate any form-related injuries and ensure efficacious exercise prescriptions and systems. Going forward, exploration exercise efforts seek to gain further quantitative data of human and system performance. Currently, methods of collecting in-flight exercise data on the ISS are limited to marker-based motion capture (MoCap) where astronauts must wear reflective markers over their clothes and specialized cameras are used. The main objective of this work was to investigate the following alternative tracking options: markerless video-based MoCap and inertial measurement units (IMUs). These were compared against traditional marker-based MoCap to evaluate kinematic accuracy and inform feasible methods for future exercise data collections on the ISS, especially in support of future Vibration Isolation and Stabilization (VIS) system development. METHODS: Three test subjects performed a variety of flight-like resistance and aerobic exercises using the Miniature Exercise Device (MED-2), Concept-2 rowing ergometer, barbell mockup, bench (e.g., for bench press, hip thruster, and cycling), and a custom structure for dips. These were intended also to represent exercises which could be performed on the multi-modality European Enhanced Exploration Exercise Device (E4D) [1]. The marker-based MoCap data, collected through a 16-camera OptiTrack MoCap system, was regarded as the gold standard to compare the data against. Passive markers were affixed to each subject according to a modified full body Plug-in Gait marker set [2] with 46 total markers. The markerless MoCap data was collected using two GoPro Hero7 cameras and one GoPro Hero11 camera. For the IMU data, a full body set of 17 Xsens DOTs were placed on the subject: 10 upper body and 7 lower body IMUs. Biomechanical modeling and evaluation was conducted through OpenSim [3] (MoCap), OpenSense [4] (IMU), OpenCap [5] (markerless), ENABLE [6] (markerless), and other modeling software. Secondary objectives included comparing the volume of equipment, reducing mass and crew set-up time. RESULTS AND DISCUSSION: While there were issues with initial processing for the IMUs and markerless MoCap, the results aided in the understanding of each sensor, developing end-to-end processes, and identifying future needs. Some observed concerns with the markerless MoCap approaches included being cognizant of a cluttered background, number of people in field of view, camera number and placement. Some challenges with the IMUs included possible sliding, early deactivation possibly due to exercise pose, and large quantity sensor synchronization. Overall, the markerless MoCap option may be the preferred method of data collection and processing as it provides a solution for certain IMU shortcomings and may be least in equipment volume, upmass, and crew setup time. CONCLUSIONS: While this work was mainly focused on ISS data collection, these sensor data along with continued evaluation and development efforts will help to establish best methods for exercise data collection on Gateway, for other Artemis missions, and beyond. Details on the latest end-to-end processing of the data and results will be presented, along with lessons learned and recommended sensor selection and methods.

S. Faragalla↗