Search NASA⌕ Search

SEARCH · Search NASA

Results for “data collection methods”

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 217 records · Page 12

Comparison of Dynamic Stability Testing Techniques with Magnetic Suspension Wind Tunnel

Dynamic stability testing techniques currently utilized at NASA Langley Research Center (LaRC) are conducted in multiple facilities and consists of free flight, forced oscillation, and free-to-oscillate tests. The MIT/NASA/ODU Magnetic Suspension and Balance System (MSBS) has been recommissioned to explore its utility as an additional facility to expand the dynamic stability test capabilities currently available at NASA LaRC. Simulations were created to replicate each current test facility and method as closely as possible. Data collected from the simulated environments was corrupted with replicated noise sources of the different testing environments and then compared to real data collected during tests when such data was available. The corrupted data was then passed through data reduction and System Identification (SID) to estimate the accuracy of the results with the known aerodynamic model that was utilized within the simulation to generate the original data. Magnitudes of noise were varied utilizing Monte Carlo analysis to perform sensitivity analysis of each noise source on the extracted dynamic stability coefficients. Some preliminary results will be presented.

Otoniel Ramirez↗

Comparison of Dynamic Stability Testing Techniques with Magnetic Suspension Wind Tunnel

Dynamic stability testing techniques currently utilized at NASA Langley Research Center (LaRC) are conducted in multiple facilities and consists of free flight, forced oscillation, and free-to-oscillate tests. The MIT/NASA/ODU Magnetic Suspension and Balance System (MSBS) has been recommissioned to explore its utility as an additional facility to expand the dynamic stability test capabilities currently available at NASA LaRC. Simulations were created to replicate each current test facility and method as closely as possible. Data collected from the simulated environments was corrupted with replicated noise sources of the different testing environments and then compared to real data collected during tests when such data was available. The corrupted data was then passed through data reduction and System Identification (SID) to estimate the accuracy of the results with the known aerodynamic model that was utilized within the simulation to generate the original data. Magnitudes of noise were varied utilizing Monte Carlo analysis to perform sensitivity analysis of each noise source on the extracted dynamic stability coefficients. Some preliminary results will be presented.

Otoniel Ramirez↗

TOWARD A METHOD FOR SCALING HUMAN BODY MODELS IN AN IMU-BASED WORKFLOW

BACKGROUND 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, these 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. For example, to measure forearm length, an IMU is placed at the wrist, the point of rotation is at the elbow, and the isolated motion is forearm flexion and extension. These calculated lengths are then used to scale models to each unique astronaut’s size, thereby improving the applicability of the model. 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. Utilizing IMUs for data collection also provides the synergistic ability to record data without a dedicated space in a room with many cameras, therefore reducing the data collection footprint, or record data where optical motion capture is not possible, such as inside a spacesuit. METHODS AND RESULTS To test this method, upper body data collection was performed with 5 Xsens DOT IMUs on a single subject. IMUs consist of an accelerometer, a gyroscope, and a magnetometer which collect linear acceleration, angular velocity, and magnetic fluctuations, respectively. Before any ground-based laboratory collection, the magnetic fluctuations are used to correct the heading of the IMU in space relative to the Earth’s magnetic field. The direct measurement of angular velocity is integrated to calculate angular acceleration. Then the linear acceleration ( a ) and angular acceleration (α) are solved using r = at/α to calculate the radius, which in this case is the distance between the IMU and the point of rotation (i.e., segment length). The IMU must be placed at the most distal point of the limb being measured (i.e., ankle if measuring lower leg length) and the test plan must consist of an isolated motion about that limb’s proximal joint (i.e., knee flexion and extension if measuring lower leg length). The distances (radii) calculated at every time interval were filtered (bandpass filter keeping 5th-90th percentile data) to eliminate outliers and spurious data that occur when the isolated motion was stopped or nearly stopped. The remaining distances were averaged, resulting in the calculated limb length. Scaling factors were then computed by dividing the calculated limb length by the unscaled model’s length. These scale factors are plugged into the Scale Tool in OpenSim [1,2] to apply the scaling to the OpenSim Full Body Rajagopal Model [3,4]. Manual measurements of limb lengths were taken before data collection started and used for comparing against the calculated lengths. The Anthropometric Survey of US Army Personnel (ANSUR II) [5] was also used as a third source of reference for limb length measurements. The following measurements were retrieved from the subject before data collection: 34.5 cm from L1 to C7 (thorax), 25.7 cm from C7 Joint Center (JC) to head vertex (neck and head), 36.3 cm from shoulder JC to elbow JC (humerus), 29.5 cm from elbow JC to wrist JC (forearm), and 16.2 cm from clavicle to acromion (clavicle). Of those five, forearm and humerus lengths were calculated using this proposed method to obtain preliminary results. The forearm length after filtering and averaging was calculated to be 37.6 cm. This is a 28% overestimation from the measured forearm length (29.5 cm). The humerus length after filtering and averaging was calculated to be 47.8 cm. This is a 31% difference from the measured subject length (36.3 cm). Sources of error include imperfect isolated motion (method currently expects that motion should be perfectly circular in a 2D plane, include no rotation of the IMU, and be relatively smooth; a more secure IMU attachment method will help), unrefined filter techniques (removed highest and lowest values with 20% high and low pass filters and no smoothing filters), arbitrary removal of stopped or near stopped data (kept data for only a short range before and after the angular velocity peaking), and a more representative method for removing gravitational acceleration is needed (current method is to zero all accelerations against a baseline taken just before the isolated motion which does not account for the gravitational acceleration changed due to IMU rotation during movement). Addressing these error sources will improve the accuracy of the limb length calculation. Next steps include creating a method for whole-body scaling estimation using individual limb scale factors. Continued pursuit of these techniques is expected to enable acquiring anthropometric information using only IMUs in real-time.

E. K. Marecki↗

Evolution of the Next Exploration Toilet through Human-in-the-Loop (HITL) Testing

Human waste collection in space is a unique and necessary function that all crewmembers must perform. The variability in how each crewmember uses the toilet to urinate and defecate introduces complexities and challenges with regards to overall hardware design. Because of this variability, it is important to consider crew inputs in all aspects of a toilet design especially with regards to crew interfaces that could impact overall waste collection. Access to crew feedback is essential to the design process and should be considered early and often through the various design phases. In 2020, NASA started a project for the Human Landing System (HLS) program to develop a Government Furnished Equipment (GFE) toilet option. The project is known as the Lavatory On-Orbit (LOO). During the early development of the LOO, the project team conducted several crew evaluations to collect and summarize valuable crew feedback on system design, function, and overall usability to influence the next design iteration. Because every person could use the system differently in space, it was extremely important to collect and analyze the data in a very methodical manner to appropriately influence the design based on the evaluation results. Establishing a standard process ensures consistent data collection from one evaluation to another, helps to maintain privacy for each test subject’s inputs and removes any potential bias from test subject to test subject. To date, the team has completed four crew evaluations on prototypes for the different LOO hardware. This paper will summarize the methodology used to conduct the evaluations as well as how data was collected and analyzed. The paper will also provide details on each of the evaluations and how the design was updated based on the results.

toilet↗

Evolution of the Next Exploration Toilet Through Human-in-the-Loop (HITL) Testing

Human waste collection in space is a unique and necessary function that all crewmembers must perform. The variability in how each crewmember uses the toilet to urinate and defecate introduces complexities and challenges with regards to overall hardware design. Because of this variability, it is important to consider crew inputs in all aspects of a toilet design especially with regards to crew interfaces that could impact overall waste collection. Access to crew feedback is essential to the design process and should be considered early and often through the various design phases. In 2020, NASA started a project for the Human Landing System (HLS) program to develop a Government Furnished Equipment (GFE) toilet option. The project is known as the Lavatory On-Orbit (LOO). During the early development of the LOO, the project team conducted several crew evaluations to collect and summarize valuable crew feedback on system design, function, and overall usability to influence the next design iteration. Because every person could use the system differently in space, it was extremely important to collect and analyze the data in a very methodical manner to appropriately influence the design based on the evaluation results. Establishing a standard process ensures consistent data collection from one evaluation to another, helps to maintain privacy for each test subject’s inputs and removes any potential bias from test subject to test subject. To date, the team has completed four crew evaluations on prototypes for the different LOO hardware. This paper will summarize the methodology used to conduct the evaluations as well as how data was collected and analyzed. The paper will also provide details on each of the evaluations and how the design was updated based on the results.

toilet↗

Evolution of the Next Exploration Toilet Through Human-in-the-Loop (HITL) Testing

Human waste collection in space is a unique and necessary function that all crewmembers must perform. The variability in how each crewmember uses the toilet to urinate and defecate introduces complexities and challenges with regards to overall hardware design. Because of this variability, it is important to consider crew inputs in all aspects of a toilet design especially with regards to crew interfaces that could impact overall waste collection. Access to crew feedback is essential to the design process and should be considered early and often through the various design phases. In 2020, NASA started a project for the Human Landing System (HLS) program to develop a Government Furnished Equipment (GFE) toilet option. The project is known as the Lavatory On-Orbit (LOO). During the early development of the LOO, the project team conducted several crew evaluations to collect and summarize valuable crew feedback on system design, function, and overall usability to influence the next design iteration. Because every person could use the system differently in space, it was extremely important to collect and analyze the data in a very methodical manner to appropriately influence the design based on the evaluation results. Establishing a standard process ensures consistent data collection from one evaluation to another, helps to maintain privacy for each test subject’s inputs and removes any potential bias from test subject to test subject. To date, the team has completed four rounds of crew evaluations with multiple crewmembers on prototypes for the different LOO subsystems. This paper will summarize the methodology used to conduct the evaluations as well as how data was collected and analyzed. The paper will also provide details on each of the evaluations and how the design was updated based on the results.

toilet↗

Evolution of the Next Exploration Toilet Through Human-in-the-Loop (HITL) Testing

Human waste collection in space is a unique and necessary function that all crewmembers must perform. The variability in how each crewmember uses the toilet to urinate and defecate introduces complexities and challenges with regards to overall hardware design. Because of this variability, it is important to consider crew inputs in all aspects of a toilet design especially with regards to crew interfaces that could impact overall waste collection. Access to crew feedback is essential to the design process and should be considered early and often through the various design phases. In 2020, NASA started a project for the Human Landing System (HLS) program to develop a Government Furnished Equipment (GFE) toilet option. The project is known as the Lavatory On-Orbit (LOO). During the early development of the LOO, the project team conducted several crew evaluations to collect and summarize valuable crew feedback on system design, function, and overall usability to influence the next design iteration. Because every person could use the system differently in space, it was extremely important to collect and analyze the data in a very methodical manner to appropriately influence the design based on the evaluation results. Establishing a standard process ensures consistent data collection from one evaluation to another, helps to maintain privacy for each test subject’s inputs and removes any potential bias from test subject to test subject. To date, the team has completed four rounds of crew evaluations with multiple crewmembers on prototypes for the different LOO subsystems. This paper will summarize the methodology used to conduct the evaluations as well as how data was collected and analyzed. The paper will also provide details on each of the evaluations and how the design was updated based on the results.

toilet↗

A Comparison of Methods Used to Estimate the Height of Sand Dunes on Mars

The collection of morphometric data on small-scale landforms from other planetary bodies is difficult. We assess four methods that can be used to estimate the height of aeolian dunes on Mars. These are (1) stereography, (2) slip face length, (3) profiling photoclinometry, and (4) Mars Orbiter Laser Altimeter (MOLA). Results show that there is good agreement among the methods when conditions are ideal. However, limitations inherent to each method inhibited their accurate application to all sites. Collectively, these techniques provide data on a range of morphometric parameters, some of which were not previously available for dunes on Mars. They include dune height, width, length, surface area, volume, and longitudinal and transverse profiles. Thc utilization of these methods will facilitate a more accurate analysis of aeolian dunes on Mars and enable comparison with dunes on other planetary surfaces.

Bourke, M. C.↗

Research and operational efforts in support of Skylab experiment M093

The objectives of Skylab Experiment M093 were to measure electrocardiographic signals during spaceflight, to elucidate the electrophysiological basis for the changes observed, and to assess the effect of the change on the human cardiovascular system. Vectorcardiographic methods were used to quantitate changes, standardize data collection, and to facilitate reduction and statistical analysis of data. In this report the authors describe the M093 experiment design, the data transmission system, data reduction methods, and the analysis of data from the three Skylab missions. The report also includes clinical applications of the techniques developed for Skylab Experiment M093.

Smith, R. F.↗

Detecting Seasonal Ice Dynamics in Satellite Images

Fully understanding how glaciers respond to environmental change will require new methods to help us identify the onset of ice acceleration events and observe how dynamic signals propagate within glaciers. In particular, observations of ice dynamics on seasonal timescales may offer insights into how a glacier interacts with various forcing mechanisms throughout the year. The task of generating continuous ice velocity time series that resolve seasonal variability is made more difficult by a spotty satellite record that contains no optical observations throughout the dark, polar winters. Furthermore, velocities obtained by feature tracking are marked by high noise when image pairs are separated by short time intervals and contain no direct insights into variability that occurs between images separated by long time intervals. In this paper, we describe a method of analyzing optical or SAR-derived feature-tracked velocities to characterize the magnitude and timing of seasonal ice dynamic variability. Our method is agnostic to data gaps and is able to recover climatological average winter velocities regardless of the availability of direct observations during winter. Using characteristic image acquisition times and error distributions from Antarctic image pairs in the ITS_LIVE dataset, we generate synthetic ice velocity time series, then apply our method to recover imposed magnitudes of seasonal variability within ±1.4 m yr−1. We then validate the techniques by comparing our results to GPS data collected on Russell Glacier in Greenland. The methods presented here may be applied to better understand how ice dynamic signals propagate on seasonal timescales, and what mechanisms control the flow of the world’s ice.

Chad A. Greene↗

Population Pharmacokinetics of Intranasal Scopolamine

Introduction: An intranasal gel dosage formulation of scopolamine (INSCOP) was developed for the treatment of Space Motion Sickness (SMS).The bioavailability and pharmacokinetics (PK) was evaluated using data collected in Phase II IND protocols. We reported earlier statistically significant gender differences in PK parameters of INSCOP at a dose level of 0.4 mg. To identify covariates that influence PK parameters of INSCOP, we examined population covariates of INSCOP PK model for 0.4 mg dose. Methods: Plasma scopolamine concentrations versus time data were collected from 20 normal healthy human subjects (11 male/9 female) after a 0.4 mg dose. Phoenix NLME was employed for PK analysis of these data using gender, body weight and age as covariates for model selection. Model selection was based on a likelihood ratio test on the difference of criteria (-2LL). Statistical significance for base model building and individual covariate analysis was set at P less than 0.05{delta(-2LL)=3.84}. Results: A one-compartment pharmacokinetic model with first-order elimination best described INSCOP concentration ]time profiles. Inclusion of gender, body weight and age as covariates individually significantly reduced -2LL by the cut-off value of 3.84(P less than 0.05) when tested against the base model. After the forward stepwise selection and backward elimination steps, gender was selected to add to the final model which had significant influence on absorption rate constant (ka) and the volume of distribution (V) of INSCOP. Conclusion: A population pharmacokinetic model for INSCOP has been identified and gender was a significant contributing covariate for the final model. The volume of distribution and Ka were significantly higher in males than in females which confirm gender-dependent pharmacokinetics of scopolamine after administration of a 0.4 mg dose.

Wu, L.↗

NASA Space Environment Analog for Training, Engineering, Science, and Technology (SEATEST) 6 Detailed Final Report

After more than 50 years since the last crewed lunar landing, plans for more missions to the moon are in development. For these missions, efficient and sustainable logistics will be critical. Additionally, innovative methods of cargo transfer to and from a lunar outpost should be considered for successfully establishing a permanent presence on the moon. SEATEST (Space Environment Analog for Training, Engineering, Science, and Technology) is an immersive mission-analogous operational atmosphere where buoyancy effects and supplemental weights can simulate partial gravity conditions similar to those astronauts will experience on the moon. SEATEST 6 took place at the University of Southern California (USC) Wrigley Marine Science Center on Santa Catalina Island from July 18-30, 2023. The analog was used to collect preliminary logistics data on two different offloading conceptual methods (a davit and a zipline) during a simulated lunar mission. Pre-test analysis indicated for a crew of two on a 14-day mission, approximately three Medium Pressurized Logistics Containers (MPLC) sized logistics containers (or a total of 37.5 single Cargo Transfer Bag Equivalents (CTBE)) would be needed to support a mission. A Computer-Aided Design (CAD) analysis was employed on the SEATEST airlock mockup to determine how many logistic containers would fit with two suited crewmembers, don/doff stands, and hatch operations. It was determined that for SEATEST, a total of 15 1.0 Small Pressurized Logistics Containers (SPLCs) and 8 2.0 SPLCs would adequately fit into the approximate 9.5 cubic meter airlock volume. This does not fully represent a complete 14-day logistic supply; however, it does provide a preliminary estimate to initiate design conversations between logistics teams and crew at this early stage of development. Data were collected in eight logistics transfer scenarios over two days with four scenarios per day. Five test subject crew participated in scenarios as pairs. Scenarios included two sizes of logistics containers – 1.0 SPLC (equivalent to a single Cargo Transfer Bag (CTB) and 2.0 SPLC (equivalent to two CTBs). Planed evaluations included the use of a logistics port compared to transfer through an Airlock hatch, offloading methods based on either a davit or a zipline system, choreography of cargo in the airlock to permit ingress and suit doffing, and dust removal protocols for an understanding of the overall impact to transfer ops. Data collected included objective data (task times for conducting overall tasks and subtasks, full audio/video of test activities, and inadvertent “dings” on hardware) and subjective data (crew consensus of: task acceptability and capability assessment ratings related to best practices, considerations, and constraints for EVA-driven logistics transfer ConOps, sim quality of the test environment, and more general debrief comments). The two logistic offloading transfer concepts (davit, zipline) presented both advantages and limitations. The davit’s flexibility in allowing the crew to pick up the containers without physical interaction was well regarded by the crew. Some limitations of select davit hardware components were noted, but the overall concept was acceptable. The zipline system proved to be the most efficient way of moving logistics from the lander to the airlock and eliminated the need for dust operations. However, extended and repetitive lifting of containers to the line could be fatiguing. In conclusion, logistics transfer could hypothetically be achieved without an offloading method; however, the time requirement for such operations would be prohibitive. Results of crew subjective feedback proposed a combined or hybrid davit/zipline method to increase efficiency.

Logistics↗

Experimental Testing of Data Fusion in A Distributed Ground-Based Sensing Network for Advanced Air Mobility

Advanced Air Mobility (AAM) is an active area of development which foresees the integration of autonomous uncrewed aircraft into the civil airspace for air transportation of people and cargo. Safe integration requires significant technological developments and extensive testing phases of sensing and surveillance strategies in dense airspace. Compared to well-assessed manned aviation systems scenarios, surveillance strategies in the AAM and small Uncrewed Aircraft Vehicles(UAVs) context need to detect smaller platforms flying at lower altitude against cluttered backgrounds in dense airspace. Fusion of data provided by a network of distributed sensing nodes is a powerful tool to enable detection and tracking in such complex conditions. This paper contributes to this research direction by proposing a surveillance strategy for the AAM environment based on sensor fusion of data acquired by distributed ground-based radars. Specifically, experimental data collected with two independent radars, observing the flight of two small UAVs, are used. Data fusion at tracking level is based on a leader-helper strategy where the leader radar uses the helper’s measurements to increase the lifespan of its generated tracks. This solution shows promising results with a 10%increase in track coverage with respect to the standalone leader radar tracking solution. The paper also proposes an interference removal processing method which is applied on the data collected by one of the two radars.

Federica Vitiello↗

Demonstration of Data Processing and Fusion from Distributed Radars for AAM Surveillance

Advanced Air Mobility (AAM) is an active area of development which foresees the integration of autonomous uncrewed aircraft into the civil airspace for air transportation of people and cargo. Safe integration requires significant technological developments and extensive testing phases of sensing and surveillance strategies in dense airspace. Compared to well-assessed manned aviation systems scenarios, surveillance strategies in the AAM and small Uncrewed Aircraft Vehicles (UAVs) context need to detect smaller platforms flying at lower altitude against cluttered backgrounds in dense airspace. Fusion of data provided by a network of distributed sensing nodes is a powerful tool to enable detection and tracking in such complex conditions. This paper contributes to this research direction by proposing a surveillance strategy for the AAM environment based on sensor fusion of data acquired by distributed ground-based radars. Specifically, experimental data collected with three independent radars, observing the flight of two small UAVs, are used. Data fusion at tracking level is based on a leader-helper strategy where the leader radar uses the helper’s measurements to increase the lifespan of its generated tracks. This solution shows promising results with a 10% increase in track coverage with respect to the standalone leader radar tracking solution. The paper also proposes an interference removal processing method which is applied on the data collected by two of the radars.

Federica Vitiello↗

Comparison Between Continuous and Intermittent Actigraphy Outcomes During Long-Duration Missions

INTRODUCTION Historically, astronauts have worn actigraphy watches continuously throughout their missions. This has enabled reliable sleep estimation and comparisons between sleep and other outcomes and mission activities such as the arrival of a visiting vehicle. However in late 2020, astronauts were scheduled to wear an actiwatch for one 2-week period every two months, substantially decreasing availability of data. Our aim was to compare sleep and mission events between data collected continuously and data collected intermittently to identify any differences. METHODS Crewmembers (n = 19) who volunteered for the NASA Standard Measures protocol between January 2019 and March 2022 were provided with actiwatches (Phillips, Respironics, Bend OR) that they wore either continuously (C; n = 9) or for two weeks every two months while in space (2W; n = 10). We used crew schedules to identify mission events that were asynchronous with actigraphy. We further compared sleep outcomes (sleep duration, wake after sleep onset [WASO], sleep efficiency) between the C and 2W actigraphy collection. RESULTS In the 2W group, sleep data was not available for 52% of EVAs, 67% of visiting vehicle events, and 67% of commander turnovers. Average sleep duration for the 2W group (M = 6.91, ± 1.24 SD) was significantly lower compared to the C group (7.51 ± 1.08, p < .01). Sleep efficiency was better for those in the C group (90.56 ± 5.19) than for those in the 2W group (87.02 ± 6.47 p < .01). There were no significant differences in WASO (C = 26.66 ±12.99; 2W = 32.38 ± 18.83). DISCUSSION Continuous actigraphy data collection yields different sleep outcomes compared to intermittent data collection. In addition, many mission events were not captured with intermittent data collection. Our findings support the use of continuous actigraphy data collection.

fatigue↗

The CapiSorb Visible System (CVS) Demonstrations on ISS

Falling liquid film amine sorbent reactors have been successfully employed to scrub CO 2 aboard submarines for decades. However, applying such proven methods aboard orbiting and coast spacecraft is significantly challenged by the nearly weightless environment, where liquid sprays and films do not fall, and vapor bubbles and gases do not rise. The Capillary Sorbent (CapiSorb) Visible System (CVS) is a technology demonstration experiment performed aboard the ISS April 18 – 21, 2023. The system establishes stable steady thin liquid film flows in Contactor (absorber) and Degasser (desorber/stripper) replacing the passive role of gravity with the combined passive roles of surface tension, wetting, and system geometry. A TOX-0 fructose ersatz liquid sorbent is employed enabling ‘transparent’ experiments performed and filmed by the crew safely in the open cabin of the ISS. Completed objectives include demonstrations of stable passive ‘massively’ parallel planar thin film capillary flows across atmospheric pressure Contactor and sealed heated Degasser. The impacts of varying flow rate, flow direction, heat input, viscosity, positive and negative Degasser pressures, condensate collection and return, fluid distribution, interfacial stability, and others are reported. At least 49 diagnostics are recorded for digitization and subsequent thermal-fluids model validation by a single HD video downlink during the nearly 22 hours of operations. An overview of the flight hardware including description of the components, diagnostics, crew procedures, flight operations, and summary of accomplishments is reported in Ref. 1. Further details of the diagnostics, tests performed, and data reduction is reported in Ref. 2. This report collects both1,2 into a single report adding methods of data digitization, reduction, and archive along with analyses and discussions of technology impacts.

microgravity↗

Simplified Vicarious Radiometric Calibration

A measurement-based radiance estimation approach for vicarious radiometric calibration of spaceborne multispectral remote sensing systems has been developed. This simplified process eliminates the use of radiative transfer codes and reduces the number of atmospheric assumptions required to perform sensor calibrations. Like prior approaches, the simplified method involves the collection of ground truth data coincident with the overpass of the remote sensing system being calibrated, but this approach differs from the prior techniques in both the nature of the data collected and the manner in which the data are processed. In traditional vicarious radiometric calibration, ground truth data are gathered using ground-viewing spectroradiometers and one or more sun photometer( s), among other instruments, located at a ground target area. The measured data from the ground-based instruments are used in radiative transfer models to estimate the top-of-atmosphere (TOA) target radiances at the time of satellite overpass. These TOA radiances are compared with the satellite sensor readings to radiometrically calibrate the sensor. Traditional vicarious radiometric calibration methods require that an atmospheric model be defined such that the ground-based observations of solar transmission and diffuse-to-global ratios are in close agreement with the radiative transfer code estimation of these parameters. This process is labor-intensive and complex, and can be prone to errors. The errors can be compounded because of approximations in the model and inaccurate assumptions about the radiative coupling between the atmosphere and the terrain. The errors can increase the uncertainty of the TOA radiance estimates used to perform the radiometric calibration. In comparison, the simplified approach does not use atmospheric radiative transfer models and involves fewer assumptions concerning the radiative transfer properties of the atmosphere. This new technique uses two neighboring uniform ground target areas having different reflectance values. The target areas can be natural or artificial and must be large enough to minimize adjacent-pixel contamination effects. The radiative coupling between the atmosphere and the terrain needs to be approximately the same for the two targets. This condition can be met for relatively uniform backgrounds when the distance between the targets is within a few hundred meters. For each target area, the radiance leaving the ground in the direction of the satellite is measured with a radiometrically calibrated spectroradiometer. Using the radiance measurements from the two targets, atmospheric adjacency and atmospheric scattering effects can be subtracted, thereby eliminating many assumptions about the atmosphere and the radiative interaction between the atmosphere and the terrain. In addition, the radiometrically calibrated spectroradiometer can be used with a known reflectance target to estimate atmospheric transmission and diffuse- to-global ratios without the need for ancillary sun photometers. Several comparisons between the simplified method and traditional techniques were found to agree within a few percent. Hence, the simplified method reduces the overall complexity of performing vicarious calibrations and can serve as a method for validating traditional radiative transfer models

Stanley, Thomas↗

Amorphous Phase Characterization Through X-Ray Diffraction Profile Modeling: Implications for Amorphous Phases in Gale Crater Rocks and Soils

The CheMin X-ray diffraction instrument on the Mars Science Laboratory rover has analyzed 18 rock and soil samples in Gale crater. Diffraction data allow for the identification of major crystalline phases based on the positions and intensities of well-defined peaks and also provides information regarding amorphous and poorly-ordered materials based on the shape and positions of broad scattering humps. The combination of diffraction data, elemental chemistry from APXS (Alpha Particle X-ray Spectrometer) and evolved gas analyses (EGA) from SAM (Sample Analysis at Mars) help constrain possible amorphous materials present in each sample (e.g., glass, opal, iron oxides, sulfates) but are model dependent. We present a novel method to characterize amorphous material in diffraction data and, through this approach, aim to characterize the phases collectively producing the amorphous profiles in CheMin diffraction data. This method may be applied to any diffraction data from samples containing X-ray amorphous materials, not just CheMin datasets, but we re-strict our discussion to Martian-relevant amorphous phases and diffraction data measured by CheMin or CheMin-like instruments.

Achilles, C. N.↗