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NASA NTRS2016

Global Positioning System Navigation Above 76,000 km for NASA's Magnetospheric Multiscale Mission

NASA's Magnetospheric Multiscale (MMS) mission, launched in March of 2015, consists of a controlled formation of four spin-stabilized spacecraft in similar highly elliptic orbits reaching apogee at radial distances of 12 and 25 Earth radii (RE) in the first and second phases of the mission. Navigation for MMS is achieved independently on-board each spacecraft by processing Global Positioning System (GPS) observables using NASA Goddard Space Flight Center (GSFC)'s Navigator GPS receiver and the Goddard Enhanced Onboard Navigation System (GEONS) extended Kalman filter software. To our knowledge, MMS constitutes, by far, the highest-altitude operational use of GPS to date and represents a high point of over a decade of high-altitude GPS navigation research and development at GSFC. In this paper we will briefly describe past and ongoing high-altitude GPS research efforts at NASA GSFC and elsewhere, provide details on the design of the MMS GPS navigation system, and present on-orbit performance data from the first phase. We extrapolate these results to predict performance in the second phase orbit, and conclude with a discussion of the implications of the MMS results for future high-altitude GPS navigation, which we believe to be broad and far-reaching.

GPS↗

NASA NTRS2016

Detached Solidification of Germanium-Silicon Crystals on the ISS

A series of Ge(sub 1-x) Si(sub x) crystal growth experiments are planned to be conducted in the Low Gradient Furnace (LGF) onboard the International Space Station. The primary objective of the research is to determine the influence of containment on the processing-induced defects and impurity incorporation in germanium-silicon alloy crystals. A comparison will be made between crystals grown by the normal and "detached" Bridgman methods and the ground-based float zone technique. Crystals grown without being in contact with a container have superior quality to otherwise similar crystals grown in direct contact with a container, especially with respect to impurity incorporation, formation of dislocations, and residual stress in crystals. "Detached" or "dewetted" Bridgman growth is similar to regular Bridgman growth in that most of the melt is in contact with the crucible wall, but the crystal is separated from the wall by a small gap, typically of the order of 10-100 microns. Long duration reduced gravity is essential to test the proposed theory of detached growth. Detached growth requires the establishment of a meniscus between the crystal and the ampoule wall. The existence of this meniscus depends on the ratio of the strength of gravity to capillary forces. On Earth, this ratio is large and stable detached growth can only be obtained over limited conditions. Crystals grown detached on the ground exhibited superior structural quality as evidenced by measurements of etch pit density, synchrotron white beam X-ray topography and double axis X-ray diffraction.

Volz, M. P.↗

NASA NTRS2016

Detached Solidification of Germanium-Silicon Crystals on the ISS

Volz, M. P.↗

NASA NTRS2017

Global Positioning System Navigation Above 76,000 km for NASA's Magnetospheric Multiscale Mission

NASA's Magnetospheric Multiscale (MMS) mission, launched in March of 2015, consists of a controlled formation of four spin-stabilized spacecraft in similar highly elliptic orbits reaching apogee at radial distances of 12 and 25 Earth radii (RE) in the first and second phases of the mission. Navigation for MMSis achieved independently on-board each spacecraft by processing Global Positioning System (GPS) observables using NASA Goddard Space Flight Center (GSFC)'s Navigator GPS receiver and the Goddard Enhanced Onboard Navigation System (GEONS) extended Kalman filter software. To our knowledge, MMS constitutes, by far, the highest-altitude operational use of GPS to date and represents a high point of over a decade of high-altitude GPS navigation research and development at GSFC. In this paper we will briefly describe past and ongoing high-altitude GPS research efforts at NASA GSFC and elsewhere, provide details on the design of the MMS GPS navigation system, and present on-orbit performance data from the first phase. We extrapolate these results to predict performance in the second phase orbit, and conclude with a discussion of the implications of the MMS results for future high-altitude GPS navigation, which we believe to be broad and far-reaching.

navigation↗

NASA NTRS2017

Influence of Containment on the Growth of Germanium-Silicon in Microgravity

A series of Ge(sub 1-x)Si(sub x) crystal growth experiments are planned to be conducted in the Low Gradient Furnace (LGF) onboard the International Space Station. The primary objective of the research is to determine the influence of containment on the processing-induced defects and impurity incorporation in germanium-silicon alloy crystals. A comparison will be made between crystals grown by the normal and 'detached' Bridgman methods and the ground-based float zone technique. 'Detached' or 'dewetted' Bridgman growth is similar to regular Bridgman growth in that most of the melt is in contact with the crucible wall, but the crystal is separated from the wall by a small gap, typically of the order of 10-100 microns. A meniscus bridges this gap between the top of the crystal and the crucible wall. Theoretical models indicate that an important parameter governing detachment is the pressure differential across this meniscus. An experimental method has been developed to control this pressure differential in microgravity that does not require connection of the ampoule volume to external gases or changes in the temperature profile during growth. Experiments will be conducted with positive, negative or zero pressure differential across the meniscus. Characterization results of ground-based experiments, including etch pit density, synchrotron white beam X-ray topography and double axis X-ray diffraction will also be described.

Volz, M. P.↗

NASA NTRSDate not supplied

MODIS Reflective Solar Band Calibration Improvements using Pseudo-Invariant Desert Targets

To provide the best science data quality, an accurate characterization of the response versus scan angle (RVS) function is critical for the MODIS reflective solar bands (RSB) on-orbit calibration. In every MODIS operational scan, the Earth’s surface, referred to here as Earth view (EV), the space view (SV) port, and the onboard calibrators are viewed via a two-sided scan mirror. The RVS is defined as the sensor’s relative response as a function the angle of incidence (AOI) to the scan mirror. Many different approaches have been developed to derive the time-dependent RVS and its look-up table (LUT) applied to MODIS Level 1B (L1B) products since calibration Collection 4. For most MODIS RSB, the on-board calibrators can reasonably track the RVS change with time. In practice, their RVS is derived using data from on-board calibrators and the EV mirror side ratio (for mirror side 2). For Terra bands 1-4, 8-10 and Aqua bands 1-4, 8-9, an enhancement has been employed in Collections 6 and 6.1 (C6/C6.1) by using Earth scene response trending from pseudo-invariant desert sites in addition to the onboard calibrators. The current C6/C6/1 RVS algorithm is focused on fitting the EV data at each AOI over time and then deriving the relative change at different AOI. The EV response trending is currently fitted with multiple segments over time. Alternatively, the EV responses can be fit first as a function of AOI before fitting temporally in order to reduce the dependence on the stability of the desert site. These pre-treatment methods on the EV data provide improvement in the derived calibration coefficients. However, evidence of insufficient calibration is still observed in the MODIS L1B reflectance data, especially in the form of differences between the mirror sides. In this paper, we review the current methodologies that utilize the EV response trends from the pseudo-invariant Libyan desert targets to supplement the gain derived from the onboard calibrators. An improvement is then proposed and investigated such that a sliding window average (SWA) is used to pre-process the raw EV data. The SWA parameters are carefully selected using trade-off studies to accurately track the Earth scene response trending in multiple cases to overcome the reflectance differences between two mirror sides. Calibration results show improvements for both Aqua and Terra MODIS RSB L1B data products. This new adjustment has been included in the recently delivered Collection 7 LUT that will be evident in the L1B products expected to be released in late 2021.

MODIS↗

NASA NTRSDate not supplied

Using Artificial Intelligence and Machine Learning to Enhance Mission Design and Operations of the Habitable Worlds Observatory (HWO)

One key aspect in the development of HWO is the early deployment of artificial intelligence (AI) and machine learning (ML) to enhance mission science and operations. Our subtask group is part of the HWO AI/ML working group and focuses on AI and ML for mission operations. Our task group seeks to educate other HWO working groups about AI and ML capabilities for mission operations, investigate how to bridge technology gaps, and enable new capabilities particularly in the areas of observational scheduling, instrument health monitoring, and downlink operations. We focus on mission tasking / scheduling both for mission analysis in development and operations. AI and ML for mission scheduling includes: tools to support proposal calls and review, ensuring fairness in calls for proposals, community peer reviews and ease workloads, as well as in-flight and ground software development (e.g., using natural language processing (NLP) to support process automation from requirements). AI and ML for the mission’s development and operations include 1) anomaly detection and prediction (from onboard and ground based tools) to monitor the spacecraft’s health, 2) ground-based automated scheduling for mission operations including long-term and short-term planning and maintenance, and 3) flight system flexible execution (as flight proven for Spitzer and JWST) to enable robust execution despite execution variations, and 4) data analysis for prioritization (e.g., real-time data evaluation leading to autonomous actions and adjustments, high-priority identification, onboard data compression, etc.). Incorporation of ML and AI will enable HWO to address the major science questions related to exoplanet characterization, general astrophysics, and solar system exploration and also extend the boundaries of space mission technologies.

Mark Moussa↗

NASA NTRS1979

Shuttle entry trajectory reconstruction using inflight accelerometer and gyro measurements

An error analysis has been made of a Shuttle postflight entry trajectory reconstruction process to obtain trajectory state estimation errors and to assess the impact of these errors on Shuttle aerodynamic force coefficient extraction. In this analysis, the entry trajectory is assumed to be reconstructed via numerical integration of onboard accelerometer and gyro measurements and constrained to satisfy ground-based radio tracking. The trajectory state estimation errors are calculated using a Kalman-Schmidt sequential filter assuming various measurement error models and combinations of ground-based tracking. The resultant trajectory estimation errors are analyzed in a simplified perturbation process to establish the accuracy to which postflight aerodynamic force coefficients can be determined. Results are presented which show that the principal error sources affecting the trajectory reconstruction and thus the force coefficient extraction, assuming perfect atmospheric density knowledge, are the accelerometer and gyro resolution, acceleration-sensitive gyro drifts, and the alignment uncertainties associated with integration on the Shuttle.

Compton, H. R.↗

NASA NTRSDate not supplied

Unlocking the Microbiome of the International Space Station

With the start of human occupation more than 22 years ago, the microbiome of International Space Station (ISS) has been monitored to assess risk to both crew and craft. Historically, this monitoring has been achieved through onboard culture and ground-based analyses. Data spanning this timeframe are descriptive of a semi-closed, human occupied environment with associations to crew changes and process escapes within the environmental control and life support systems. While this approach has served to provide alerts to anomalies and overall confidence in the controls in place, the data are limited to the media type and growth conditions used. The bias toward the detection of culturable organisms has depicted an overall lack in biodiversity. As NASA leaves the ISS to focus on exploration, it is critical to fully understand its microbiome and its possible association to the noted positive influence on crew and vehicle health. The implementation of culture-independent, nanopore sequencing-based studies, both onboard the ISS and with returned ground samples, is revealing a more thorough depiction of the microbiome. As noted with pervious culture-based data, there is a common core microbiome across time and location, but key distinct areas of greater diversity exist. Through further investigation, these areas are emerging as unique ecological niches, potentially resulting in environmentally driven microbial selection. Moreover, the presence of some noted taxa within these unique locations has implications for crew health, planetary protection, and controls used in future spacecraft systems. The ability to perform in situ profiling of the ISS microbiome is transforming how NASA assesses risk and is a critical tool towards monitoring the establishment of the environmental microbiome in exploration spacecraft.

Sarah Stahl-Rommel↗

NASA NTRSDate not supplied

Content and Representation of Information Needed to Support Time-Constrained Problem Solving

NASA’s current mission-operations paradigm originated with Project Mercury and endured with minimum evolution through the Apollo Program, Space Shuttle Program, and ISS missions. At its foundation is a near-complete real-time dependence on a ground team to manage the combined state of the mission, vehicle, and crew. Utilizing many engineers and operators with broad and deep expertise; large, distributed datasets including extensive telemetry; and expansive analytical and computing power, this ground team has served as the safety net for crewed spaceflight missions over the past 60 years. This approach must change to address challenges associated with missions beyond low Earth orbit (BLEO), including infrequent resupply, reduced ability to evacuate, and delayed communications that prohibit real-time operational support. We anticipate that a necessary part of this change will be increased independence for the crew, as roles and responsibilities traditionally performed by ground teams move on board the vehicle. While many risks are associated with Earth-independent operations, one particular concern is ensuring that the crew will have adequate onboard support to perform urgent problem solving when communication with the ground is delayed or intermittent. A key resource that enables the ground team to respond to anomalies quickly and effectively is the extraordinary expertise and experience it possesses. It is comprised of 80+ experts on at any given time, with a combined 600+ years of system-specific experience across 22 unique console disciplines. A small crew will face the unprecedented challenge of independently responding to anomalies that have historically been handled by a team 20 times their size. Another important resource upon which the ground heavily relies to support procedure execution and anomaly response is data. The amount of telemetry data that each flight controller monitors is extensive. In addition, as the ground team works to further assess impacts, trouble shoot, identify workarounds, and oversee procedure execution, it accesses and synthesizes engineering and procedure information, as well as system build, test, and configuration documentation. It is not feasible nor useful to put all these data onboard as crews become more Earth independent. Each member of a small Mars mission small crew will have multiple roles beyond monitoring telemetry and data gathering, and multiple roles within anomaly resolution processes, thereby limiting their capacity for copious amounts of information. Moreover, while access is necessary, it alone is insufficient. Information will need to be compiled, refined, and represented appropriately to support the crew’s reduced attention and expertise. This work seeks to understand the content and representation of information needed to support time-constrained problem solving and decision making by the crew without real-time ground support. To build this understanding, we first surveyed the literature, focusing on how expert problem solvers construct and manipulate their mental models. Next, we interviewed expert problem solvers in spaceflight and analogous domains and surveyed industry solutions for data presentation. Finally, we analyzed current spaceflight operations by investigating flight controller anomaly resolution processes during ISS training simulations and real operational events. These methods led to creating a problem-solving framework that details common themes and features of attending to, assessing, analyzing, and acting on problems in complex, time-constrained domains. Using this framework and the results of our analysis, we identified conceptual data representations needed for crew-led problem-solving. Preliminary onboard user interface concepts to meet identified needs will be presented.

anomaly response↗

NASA NTRS1999

Autonomous Onboard Science Image Analysis for Future Mars Rover Missions

To explore high priority landing sites and to prepare for eventual human exploration, future Mars missions will involve rovers capable of traversing tens of kilometers. However, the current process by which scientists interact with a rover does not scale to such distances. Specifically, numerous command cycles are required to complete even simple tasks, such as, pointing the spectrometer at a variety of nearby rocks. In addition, the time required by scientists to interpret image data before new commands can be given and the limited amount of data that can be downlinked during a given command cycle constrain rover mobility and achievement of science goals. Experience with rover tests on Earth supports these concerns. As a result, traverses to science sites as identified in orbital images would require numerous science command cycles over a period of many weeks, months or even years, perhaps exceeding rover design life and other constraints. Autonomous onboard science analysis can address these problems in two ways. First, it will allow the rover to transmit only "interesting" images, defined as those likely to have higher science content. Second, the rover will be able to anticipate future commands. For example, a rover might autonomously acquire and return spectra of "interesting" rocks along with a high resolution image of those rocks in addition to returning the context images in which they were detected. Such approaches, coupled with appropriate navigational software, help to address both the data volume and command cycle bottlenecks that limit both rover mobility and science yield. We are developing fast, autonomous algorithms to enable such intelligent on-board decision making by spacecraft. Autonomous algorithms developed to date have the ability to identify rocks and layers in a scene, locate the horizon, and compress multi-spectral image data. Output from these algorithms could be used to autonomously obtain rock spectra, determine which images should be transmitted to the ground, or to aid in image compression. We will discuss these and other algorithms and demonstrate their performance during a recent rover field test.

Gulick, V. C.↗

NASA NTRS2021

Real-Time Culture-Independent Microbial Profiling Onboard the International Space Station using Nanopore Sequencing

For the past two decades, microbial monitoring of the International Space Station (ISS) has relied on culture-dependent methods that require return to Earth for analysis. This has a number of limitations, with the most significant being bias towards the detection of culturable organisms and the inherent delay between sample collection and ground-based analysis. In recent years, portable and easy-to-use molecular-based tools, such as Oxford Nanopore Technologies’ MinION™ sequencer and miniPCR bio’s miniPCR™ thermal cycler, have been validated onboard the ISS. Here, we report on the development, validation, and implementation of a swab-to-sequencer method that provides a culture-independent solution to real-time microbial profiling onboard the ISS. Method development focused on analysis of swabs collected in a low-biomass environment with limited facility resources and stringent controls on allowed processes and reagents. ISS-optimized procedures included enzymatic DNA extraction from a swab tip, bead-based purifications, altered buffers, and the use of miniPCR and the MinION. Validation was conducted through extensive ground-based assessments comparing current standard culture-dependent and newly developed culture-independent methods. Similar microbial distributions were observed between the two methods; however, as expected, the culture-independent data revealed microbial profiles with greater diversity. Protocol optimization and verification was established during NASA Extreme Environment Mission Operations (NEEMO) analog missions 21 and 22, respectively. Unique microbial profiles obtained from analog testing validated the swab-to-sequencer method in an extreme environment. Finally, four independent swab-to-sequencer experiments were conducted onboard the ISS by two crewmembers. Microorganisms identified from ISS swabs were consistent with historical culture-based data, and primarily consisted of commonly observed human-associated microbes. This simplified method has been streamlined for high ease-of-use for a non-trained crew to complete in an extreme environment, thereby enabling environmental and human health diagnostics in real-time as future missions take us beyond low-Earth orbit.

microbiology↗

NASA NTRS1998

DC-8 Scanning Lidar Characterization of Aircraft Contrails and Cirrus Clouds

An angular-scanning large-aperture (36 cm) backscatter lidar was developed and deployed on the NASA DC-8 research aircraft as part of the SUCCESS (Subsonic Aircraft: Contrail and Cloud Effects Special Study) program. The lidar viewing direction could be scanned continuously during aircraft flight from vertically upward to forward to vertically downward, or the viewing could be at fixed angles. Real-time pictorial displays generated from the lidar signatures were broadcast on the DC-8 video network and used to locate clouds and contrails above, ahead of, and below the DC-8 to depict their spatial structure and to help select DC-8 altitudes for achieving optimum sampling by onboard in situ sensors. Several lidar receiver systems and real-time data displays were evaluated to help extend in situ data into vertical dimensions and to help establish possible lidar configurations and applications on future missions. Digital lidar signatures were recorded on 8 mm Exabyte tape and generated real-time displays were recorded on 8mm video tape. The digital records were transcribed in a common format to compact disks to facilitate data analysis and delivery to SUCCESS participants. Data selected from the real-time display video recordings were processed for publication-quality displays incorporating several standard lidar data corrections. Data examples are presented that illustrate: (1) correlation with particulate, gas, and radiometric measurements made by onboard sensors, (2) discrimination and identification between contrails observed by onboard sensors, (3) high-altitude (13 km) scattering layer that exhibits greatly enhanced vertical backscatter relative to off-vertical backscatter, and (4) mapping of vertical distributions of individual precipitating ice crystals and their capture by cloud layers. An angular scan plotting program was developed that accounts for DC-8 pitch and velocity.

Uthe, Edward E.↗

NASA NTRS1974

The particle background observed by the X-ray detectors onboard Copernicus

The design and characteristics of low energy detectors on the Copernicus satellite are described. The functions of the sensors in obtaining data on the particle background. The procedure for processing the data obtained by the satellite is examined. The most significant positive deviations are caused by known weak X-ray sources in the field of view. In addition to small systemic effects, occasional random effects where the count rate increases suddenly and decreases within a few frames are analyzed.

Davison, P. J. N.↗

NASA NTRS2020

Introduction to ISS Crew Displays

The International Space Station (ISS) began payload operations in earnest in 2000 with the arrival of the Expedition 1. To date, ISS has offered Principal Investigators (PIs) a reliable platform for microgravity research, having hosted thousands of onboard science experiments. Most of this research is supported by experiment hardware and software and many include a crew‐operated Graphical User Interface (GUI). The purpose of this article is to share information with PIs and Payload Developer (PD) teams about the processes, standards, and guidelines applicable to crew GUI design that must be complied with when planning payload software. The goal is not to enumerate all of the ISS display standards, but rather to highlight design guidelines and the ISS Program milestones for verification and approval of onboard crew displays.

Graphical User Interface↗

NASA NTRS1977

Integrated payload and mission planning, phase 3. Volume 3: Ground real-time mission operations

The payloads tentatively planned to fly on the first two Spacelab missions were analyzed to examine the cost relationships of providing mission operations support from onboard vs the ground-based Payload Operations Control Center (POCC). The quantitative results indicate that use of a POCC, with data processing capability, to support real-time mission operations is the most cost effective case.

White, W. J.↗

NASA NTRS1980

CCD data processor for maximum likelihood feature classification

The paper describes an advanced technology development which utilizes a high speed analog/binary CCD correlator to perform the matrix multiplications necessary to implement onboard feature classification. The matrix manipulation module uses the maximum likelihood classification algorithm assuming a Gaussian probability density function. The module will process 16 element multispectral vectors at rates in excess of 500 thousand multispectral vector elements per second. System design considerations for the optimum use of this module are discussed, test results from initial device fabrication runs are presented, and the performance in typical processing applications is described

Benz, H. F.↗

NASA NTRS1992

Multi-layer holographic bifurcative neural network system for real-time adaptive EOS data analysis

Optical data processing techniques have the inherent advantage of high data throughout, low weight and low power requirements. These features are particularly desirable for onboard spacecraft in-situ real-time data analysis and data compression applications. The proposed multi-layer optical holographic neural net pattern recognition technique will utilize the nonlinear photorefractive devices for real-time adaptive learning to classify input data content and recognize unexpected features. Information can be stored either in analog or digital form in a nonlinear photorefractive device. The recording can be accomplished in time scales ranging from milliseconds to microseconds. When a system consisting of these devices is organized in a multi-layer structure, a feed forward neural net with bifurcating data classification capability is formed. The interdisciplinary research will involve the collaboration with top digital computer architecture experts at the University of Southern California.

Liu, Hua-Kuang↗