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Getting a Cohesive Answer from a Common Start: Scalable Multidisciplinary Analysis through Transformation of a System Model

One of the challenges of systems engineering is in working multidisciplinary problems in a cohesive manner. When planning analysis of these problems, system engineers must tradeoff time and cost for analysis quality and quantity. The quality is associated with the fidelity of the multidisciplinary models and the quantity is associated with the design space that can be analyzed. The tradeoff is due to the resource intensive process of creating a cohesive multidisciplinary system model and analysis. Furthermore, reuse or extension of the models used in one stage of a product life cycle for another is a major challenge. Recent developments have enabled a much less resource-intensive and more rigorous approach than handwritten translation scripts or codes of multidisciplinary models and their analyses. The key is to work from a core system model defined in a MOF-based language such as SysML and in leveraging the emerging tool ecosystem, such as Query-View- Transform (QVT), from the OMG community. SysML was designed to model multidisciplinary systems and analyses. The QVT standard was designed to transform SysML models. The Europa Hability Mission (EHM) team has begun to exploit these capabilities. In one case, a Matlab/Simulink model is generated on the fly from a system description for power analysis written in SysML. In a more general case, a symbolic mathematical framework (supported by Wolfram Mathematica) is coordinated by data objects transformed from the system model, enabling extremely flexible and powerful tradespace exploration and analytical investigations of expected system performance.

Cole, Bjorn↗

Intrinsic Dimensionality as a Metric for the Impact of Mission Design Parameters

High-resolution space-based spectral imaging of the Earth's surface delivers critical information for monitoring changes in the Earth system as well as resource management and utilization. Orbiting spectrometers are built according to multiple design parameters, including ground sampling distance (GSD), spectral resolution, temporal resolution, and signal-to-noise ratio. Different applications drive divergent instrument designs, so optimization for wide-reaching missions is complex. The Surface Biology and Geology component of NASA's Earth System Observatory addresses science questions and meets applications needs across diverse fields, including terrestrial and aquatic ecosystems, natural disasters, and the cryosphere. The algorithms required to generate the geophysical variables from the observed spectral imagery each have their own inherent dependencies and sensitivities, and weighting these objectively is challenging. Here, we introduce intrinsic dimensionality (ID), a measure of information content, as an applications-agnostic, data-driven metric to quantify performance sensitivity to various design parameters. ID is computed through the analysis of the eigenvalues of the image covariance matrix, and can be thought of as the number of significant principal components. This metric is extremely powerful for quantifying the information content in high-dimensional data, such as spectrally resolved radiances and their changes over space and time. We find that the ID decreases for coarser GSD, decreased spectral resolution and range, less frequent acquisitions, and lower signal-to-noise levels. This decrease in information content has implications for all derived products. ID is simple to compute, providing a single quantitative standard to evaluate combinations of design parameters, irrespective of higher-level algorithms, products, applications, or disciplines.

Intrinsic dimensionality↗

Summary of Technical Interchange Meetings (TIMs) Designed to Enable Earth Independent Medical Operations (EIMO)

The Exploration Medical Capability Element (ExMC) in NASA’s Human Research Program hosted a series of TIMs in 2023-2024 designed to stimulate discussion around specific topics with the goal of enabling EIMO. In context of the thematic constituent elements of EIMO, namely pre-mission planning, acute/emergent/prolonged medical decision making, supply/resource management and task load management, subject matter experts from industry, academia and government (NASA and other Agencies) provided valuable and actionable guidance and recommendations. Earth-based medical experts will remain indispensable for pre-mission planning, however, management of acute/emergent medical contingencies will require a gradual transition of medical care and decision making from terrestrial to space-based assets to enable support of astronaut health and performance and reduce overall mission risk. Key to achieving these enhancements is providing an integrated data system platform capable of utilizing multiple data streams in concert with a variety of on-board databases and passive monitoring of video and wearable sensors to enable a multi-modal, agentic AI-based clinical decision support system (CDSS) to support crew medical officer (CMO) medical decision-making. The EIMO series of TIMs (I-V) have proven to be instructive and portend a significant paradigm shift will be necessary to maintain crew health and performance on exploration class missions. Importantly, since the expected paradigm shift will be significantly different from the methods of operation that have been employed for the majority of missions from the inception of human spaceflight to date, any proposed methods must be deployed in the setting of ongoing operations early and be “tested, reviewed and practiced” while reliable back-up is available to facilitate an Enterprise-wide level of comfort and acceptance. Serious constraints on data transmission coupled with a large and expanding universe of on-board medical informatics data streams will necessitate implementation of a CDSS to supplant the current reliance on support provided by ground-based SMEs. Establishment of trust in the system by CMO/crew and the ground-based medical support team will be essential. Co-development of a CDSS with industry partners will assure that state of the art tools can be employed, and industry efficiencies can be leveraged. Training regimens, materials and tools must evolve to be responsive (just-in-time training) and facilitate autonomous execution of procedures. Proficiency metrics should be established and be based on validated competencies or milestones as opposed to a prescribed number of training hours. Training should be prioritized for broad, translatable skills that have universal application across a variety of medical conditions. Repetition was deemed to be the key to achieving proficiency and emphasis should lie in procedural training which is known to extinguish more rapidly than diagnostic skills. Advanced tools, e.g., extended reality, can provide more realistic and effective training. Use of advanced probabilistic risk assessment tools will be essential to optimize the medical system capability while carefully balancing risk relative to mass/power/volume limitations. Importance of factoring use-life of medical supplies and maintaining awareness of redundancy and opportunity to re-purpose under off nominal situations was emphasized. Consideration of adopting optimized performance standards vs. “good-enough” performance thresholds is warranted. The use of legacy systems as opposed to creating new systems may be preferable. Managing task load and associated cognitive load will be essential to maintain operational safety and behavioral health. ExMC aspires to create a shared EIMO paradigm and strategic vision for advancing medical system design through novel technologies, training, protocols, and support capabilities, built upon the spirit of successful strategies and innovations over the past six decades of space medicine operations.

Jay Lemery↗

Automatic mathematical modeling for real time simulation system

A methodology for automatic mathematical modeling and generating simulation models is described. The models will be verified by running in a test environment using standard profiles with the results compared against known results. The major objective is to create a user friendly environment for engineers to design, maintain, and verify their model and also automatically convert the mathematical model into conventional code for conventional computation. A demonstration program was designed for modeling the Space Shuttle Main Engine Simulation. It is written in LISP and MACSYMA and runs on a Symbolic 3670 Lisp Machine. The program provides a very friendly and well organized environment for engineers to build a knowledge base for base equations and general information. It contains an initial set of component process elements for the Space Shuttle Main Engine Simulation and a questionnaire that allows the engineer to answer a set of questions to specify a particular model. The system is then able to automatically generate the model and FORTRAN code. The future goal which is under construction is to download the FORTRAN code to VAX/VMS system for conventional computation. The SSME mathematical model will be verified in a test environment and the solution compared with the real data profile. The use of artificial intelligence techniques has shown that the process of the simulation modeling can be simplified.

Wang, Caroline↗

Modulation Classification of Satellite Communication Signals Using Cumulants and Neural Networks

National Aeronautics and Space Administration (NASA)'s future communication architecture is evaluating cognitive technologies and increased system intelligence. These technologies are expected to reduce the operational complexity of the network, increase science data return, and reduce interference to self and others. In order to increase situational awareness, signal classification algorithms could be applied to identify users and distinguish sources of interference. A significant amount of previous work has been done in the area of automatic signal classification for military and commercial applications. As a preliminary step, we seek to develop a system with the ability to discern signals typically encountered in satellite communication. Proposed is an automatic modulation classifier which utilizes higher order statistics (cumulants) and an estimate of the signal-to-noise ratio. These features are extracted from baseband symbols and then processed by a neural network for classification. The modulation types considered are phase-shift keying (PSK), amplitude and phase-shift keying (APSK),and quadrature amplitude modulation (QAM). Physical layer properties specific to the Digital Video Broadcasting - Satellite- Second Generation (DVB-S2) standard, such as pilots and variable ring ratios, are also considered. This paper will provide simulation results of a candidate modulation classifier, and performance will be evaluated over a range of signal-to-noise ratios, frequency offsets, and nonlinear amplifier distortions.

Signal Recognition↗

Modulation Classification of Satellite Communication Signals Using Cumulants and Neural Networks

National Aeronautics and Space Administration (NASA)'s future communication architecture is evaluating cognitive technologies and increased system intelligence. These technologies are expected to reduce the operational complexity of the network, increase science data return, and reduce interference to self and others. In order to increase situational awareness, signal classification algorithms could be applied to identify users and distinguish sources of interference. A significant amount of previous work has been done in the area of automatic signal classification for military and commercial applications. As a preliminary step, we seek to develop a system with the ability to discern signals typically encountered in satellite communication. Proposed is an automatic modulation classifier which utilizes higher order statistics (cumulants) and an estimate of the signal-to-noise ratio. These features are extracted from baseband symbols and then processed by a neural network for classification. The modulation types considered are phase-shift keying (PSK), amplitude and phase-shift keying (APSK),and quadrature amplitude modulation (QAM). Physical layer properties specific to the Digital Video Broadcasting - Satellite- Second Generation (DVB-S2) standard, such as pilots and variable ring ratios, are also considered. This paper will provide simulation results of a candidate modulation classifier, and performance will be evaluated over a range of signal-to-noise ratios, frequency offsets, and nonlinear amplifier distortions.

Signal Classification↗

JPSS-2 VIIRS Pre-Launch Reflective Solar Band Testing and Performance

The Visible Infrared Imaging Radiometer Suite (VIIRS) instruments on-board the Suomi National Polar-orbiting Partnership (S-NPP) and Joint Polar Satellite System (JPSS) spacecrafts 1 and 2 provides calibrated sensor data record (SDR) reflectance, radiance, and brightness temperatures for use in environment data record (EDR) products. The SDRs and EDRs are used in weather forecasting models, weather imagery and climate applications such as ocean color, sea surface temperature and active fires. The VIIRS has 22 bands covering a spectral range 0.4–12.4 m with resolutions of 375 m and 750 m for imaging and moderate bands respectively on four focal planes. The bands are stratified into three different types based on the source of energy sensed by the bands. The reflective solar bands (RSBs) detect sunlight reflected from the Earth, thermal emissive bands (TEBs) sense emitted energy from the Earth and the day/night band (DNB) detects both solar and lunar reflected energy from the Earth. The SDR calibration uses a combination of pre-launch testing and the solar diffuser (SD), on-board calibrator blackbody (OBCBB) and space view (SV) on-orbit calibrator sources. The pre-launch testing transfers the National Institute of Standards and Technology (NIST) traceable calibration to the SD, for the RSB, and the OBCBB, for the TEB. Post-launch, the on-board calibrators track the changes in instrument response and adjust the SDR product as necessary to maintain the calibration. This paper will discuss the pre-launch radiometric calibration portion of the SDR calibration for the RSBs that includes the dynamic range, detector noise, calibration coefficients and radiometric uncertainties for JPSS-2 VIIRS.

JPSS↗

Low Power Transceiver

One of the FREESTAR experiments, the Low Power Transceiver (LPT) experiment is a low-power, lightweight software programmable transceiver prototype technology demonstration that is being developed by NASA as a low-cost S-band spacecraft navigation and communication device. The LPT prototype receives Global Positioning System (GPS) satellite signals for spacecraft navigation support and provides both forward and return, low-rate data communications links to the Merritt Island (MILA) and Dryden Flight Research Facility (DFRC) ground stations and to the Tracking and Data Relay Satellite System (TDRSS). The experiment is designed to demonstrate the system's ability to do simultaneous communications and navigation, as well as multi-mode communications and reconfiguration. LPT is managed by NASA's Goddard Space Flight Center and sponsored by NASA/HQ Code M. The LPT experiment consists of one thermally conductive box containing the electronics stack, three S-band antennas and one L-band antenna. The LPT payload uses general Orbiter services, including power control, command, and telemetry provided through the HHC avionics. On-orbit, the LPT payload will be primarily operated via direct communications between LPT and ground stations (MILA, WLPS, or DFRC) and/or TDRSS, with backup command and telemetry capability provided via the hitchhiker avionics and remote Payload Operations Control Center. During operations, LPT will utilize high Sband frequencies for communications. The LPT TDRSS (and GN) forward link (uplink) frequency is 2106.40625 MHz and their TDRSS (and GN) return link (downlink) frequency is 2287.5 MHz (utilizing Left-handed Circular Polarization to work with the TDRSS MA system). Two standard switch panel switches will be utilized to prohibit inadvertent operation of the antenna. An additional inhibit will be provided through the HH avionics power relay to the LPT.

Source record↗

Vacuum Pump-Down of the Annular Insulation Space for Large Field-Erected Liquid Hydrogen Storage Tanks

Insulation systems are critical to liquid hydrogen storage tank performance. Tanks in the capacity range of 100 to 1,000 m 3 are typically shop built and designed with high-vacuum (HV) multi-layer insulation (MLI), whereas storage vessels larger than 1,000 m 3 are typically field-erected and supplied with bulk fill insulation working at moderate vacuum (MV) levels (1-100 millitorr). For large, field-erected vessels, two types of bulk fill insulation typically used: perlite and hollow glass microspheres (glass bubbles). Selection of either material is driven by a tradeoff between CAPEX and OPEX, such as the material and construction cost versus operating thermal performance and maintenance. In either case, the vacuum level needed to achieve optimum performance is likely to drive the field testing and commissioning portion of the construction schedule. A primary goal of this paper is to present practical experience and data for warm vacuum pressure (WVP) and cold vacuum pressure (CVP) levels. Recommended WVP levels needed prior to cooldown consider both perlite powder and glass bubbles. Pumping time expected to achieve target vacuum levels, considering a variety of factors, is also discussed. Recommendations for a standard practice in vacuum-insulated tank commissioning are based on historical NASA data, and those collected during recent projects.

A M Swanger↗

Using the Flow-3D General Moving Object Model to Simulate Coupled Liquid Slosh - Container Dynamics on the SPHERES Slosh Experiment: Aboard the International Space Station

The SPHERES Slosh Experiment (SSE) is a free floating experimental platform developed for the acquisition of long duration liquid slosh data aboard the International Space Station (ISS). The data sets collected will be used to benchmark numerical models to aid in the design of rocket and spacecraft propulsion systems. Utilizing two SPHERES Satellites, the experiment will be moved through different maneuvers designed to induce liquid slosh in the experiment's internal tank. The SSE has a total of twenty-four thrusters to move the experiment. In order to design slosh generating maneuvers, a parametric study with three maneuvers types was conducted using the General Moving Object (GMO) model in Flow-30. The three types of maneuvers are a translation maneuver, a rotation maneuver and a combined rotation translation maneuver. The effectiveness of each maneuver to generate slosh is determined by the deviation of the experiment's trajectory as compared to a dry mass trajectory. To fully capture the effect of liquid re-distribution on experiment trajectory, each thruster is modeled as an independent force point in the Flow-3D simulation. This is accomplished by modifying the total number of independent forces in the GMO model from the standard five to twenty-four. Results demonstrate that the most effective slosh generating maneuvers for all motions occurs when SSE thrusters are producing the highest changes in SSE acceleration. The results also demonstrate that several centimeters of trajectory deviation between the dry and slosh cases occur during the maneuvers; while these deviations seem small, they are measureable by SSE instrumentation.

Schulman, Richard↗

SpaceCubeX: A Framework for Evaluating Hybrid Multi-Core CPU FPGA DSP Architectures

The SpaceCubeX project is motivated by the need for high performance, modular, and scalable on-board processing to help scientists answer critical 21st century questions about global climate change, air quality, ocean health, and ecosystem dynamics, while adding new capabilities such as low-latency data products for extreme event warnings. These goals translate into on-board processing throughput requirements that are on the order of 100-1,000 more than those of previous Earth Science missions for standard processing, compression, storage, and downlink operations. To study possible future architectures to achieve these performance requirements, the SpaceCubeX project provides an evolvable testbed and framework that enables a focused design space exploration of candidate hybrid CPU/FPGA/DSP processing architectures. The framework includes ArchGen, an architecture generator tool populated with candidate architecture components, performance models, and IP cores, that allows an end user to specify the type, number, and connectivity of a hybrid architecture. The framework requires minimal extensions to integrate new processors, such as the anticipated High Performance Spaceflight Computer (HPSC), reducing time to initiate benchmarking by months. To evaluate the framework, we leverage a wide suite of high performance embedded computing benchmarks and Earth science scenarios to ensure robust architecture characterization. We report on our projects Year 1 efforts and demonstrate the capabilities across four simulation testbed models, a baseline SpaceCube 2.0 system, a dual ARM A9 processor system, a hybrid quad ARM A53 and FPGA system, and a hybrid quad ARM A53 and DSP system.

Hybrid Flight Architectures↗

Quantitative Comparison of Proprietary and Open-Source Georeferencing Tools for Use with Astronaut Photography

The Crew Earth Observations (CEO) Facility within the Earth Science and Remote Sensing Unit at NASA’s Johnson Space Center supports the acquisition, analysis, and curation of astronaut photography of Earth’s surface and atmosphere. Astronauts on the International Space Station (ISS) respond to requests from CEO to acquire imagery of scientific and education targets, to include high profile targets in response to activations from the International Charter for Space & Major Disasters (also known as the International Disaster Charter, or IDC) and NASA’s Disasters Program. CEO facilitates the acquisition of astronaut photography in response to IDC events and delivers georeferenced data products to the United States Geological Survey (USGS) for distribution to the disaster community. Using GeoRef, an internal web-based tool developed in collaboration with NASA’s Ames Research Center, CEO generates data packages of georeferenced imagery, uncertainty images for assessing control and tie point accuracy, and metadata documenting raw and processed data. Operational experience with the Georef software identified vulnerabilities to internal code and server errors that can significantly increase time of data production. As such, CEO developed a backup procedure in case the GeoRef software experiences front-end or back-end errors. A system using OSGEO’s open-source QGIS software combined with a semi-automated pipeline using the object-oriented Python language and the Geospatial Abstract Library for generating metadata is quantitatively compared to GeoRef’s data package for quality and productivity. Root Mean Square Error (RMSE) provides a standard measurement of data quality as it relates to ground error. Assessing RMSE measurements generated from georeferenced astronaut photographs acquired with different obliquity and focal length offers a comprehensive accuracy assessment of the software’s transformation algorithms. This assessment will indicate the software's ability to produce data products with the least ground-error or highest data quality regarding ground accuracy. In addition, a comparison of the software’s efficiency in generating a data package that includes georeferenced images, metadata, and uncertainty images for measuring tie/ground point error was performed. Initial results, based on the comparison of three nadir-facing astronaut photographs acquired with a 95mm focal length, reveal the QGIS-based system's average RMSE is 2.36 (pixels) suggesting its georectification system produces data products that meet and perhaps improve upon Georef solution's average RMSE of 32.99 (pixels). However, the QGIS system was unable to reproduce two unique Georef data products, uncertainty images for measuring tie and control point errors and a translated unwrapped image. In addition, the Georef software is designed to accept handheld camera pose information from a hardware component (Geosens) scheduled for deployment on the ISS in late 2018; this information is intended to provide increased accuracy and auto-registration capability for astronaut photographs. Future work is expected to determine the QGIS-based georectification system’s potential as an open-source alternative (and operational backup) to Georef for georeferencing the full range of resolutions and viewing angles unique to handheld digital camera imagery in support of ISS disaster response activities.

Jagge, Amy M.↗

Merged and Gridded GPM and Atmospheric River Data Product

The Global Precipitation Measurement (GPM) Mission Core Observatory satellite launched in 2014 as a joint mission between National Aeronautics and Space Administration (NASA) and JAXA. Global Precipitation Measurement (GPM) has, since that time, provided continuous, valuable dual-frequency radar and passive microwave radiometer observations. Here, we introduce a gridded data set of collocated GPM Core Observatory observational products merged with a reanalysis-derived Atmospheric river (AR) data set in the North Atlantic and North Pacific sectors. The three data sets that are merged and gridded are: (a) the NASA Goddard Profiling (GPROF) precipitation product, which uses GPM passive microwave radiometer observations to derive surface precipitation rates, (b) a water vapor data product derived from the GPM Core Observatory radiometer, provided by Remote Sensing Systems (RSS), and (c) the Mattingly et al. (2018, https://doi.org/10.1029/2018jd028714) AR data set that is specifically tuned to the high-latitude regions. This novel merged data set spans from May 2014 to December 2022 with plans to update annually through 2026 at minimum. This gridded product combines RSS passive water vapor and precipitation estimates with coincident AR detection. This data product benefits the scientific community by providing (a) user-friendly gridded satellite data compared to standard satellite data sets, while maintaining high temporal resolution, and (b) coincident satellite observations to assess the link between ARs and precipitation.

Marian E Mateling↗

Making tomorrow's mistakes today: Evolutionary prototyping for risk reduction and shorter development time

In the early days of JPL's solar system exploration, each spacecraft mission required its own dedicated data system with all software applications written in the mainframe's native assembly language. Although these early telemetry processing systems were a triumph of engineering in their day, since that time the computer industry has advanced to the point where it is now advantageous to replace these systems with more modern technology. The Space Flight Operations Center (SFOC) Prototype group was established in 1985 as a workstation and software laboratory. The charter of the lab was to determine if it was possible to construct a multimission telemetry processing system using commercial, off-the-shelf computers that communicated via networks. The staff of the lab mirrored that of a typical skunk works operation -- a small, multi-disciplinary team with a great deal of autonomy that could get complex tasks done quickly. In an effort to determine which approaches would be useful, the prototype group experimented with all types of operating systems, inter-process communication mechanisms, network protocols, packet size parameters. Out of that pioneering work came the confidence that a multi-mission telemetry processing system could be built using high-level languages running in a heterogeneous, networked workstation environment. Experience revealed that the operating systems on all nodes should be similar (i.e., all VMS or all PC-DOS or all UNIX), and that a unique Data Transport Subsystem tool needed to be built to address the incompatibilities of network standards, byte ordering, and socket buffering. The advantages of building a telemetry processing system based on emerging industry standards were numerous: by employing these standards, we would no longer be locked into a single vendor. When new technology came to market which offered ten times the performance at one eighth the cost, it would be possible to attach the new machine to the network, re-compile the application code, and run. In addition, we would no longer be plagued with lack of manufacturer support when we encountered obscure bugs. And maybe, hopefully, the eternal elusive goal of software portability across different vendors' platforms would finally be available. Some highlights of our prototyping efforts are described.

Friedman, Gary↗

Determining the Probability of Violating Upper-Level Wind Constraints for the Launch of Minuteman III Ballistic Missiles at Vandenberg Air Force Base

The 30th Operational Support Squadron Weather Flight (30 OSSWF) provides comprehensive weather services to the space program at Vandenberg Air Force Base (VAFB) in California. One of their responsibilities is to monitor upper-level winds to ensure safe launch operations of the Minuteman Ill ballistic missile. The 30 OSSWF tasked the Applied Meteorology Unit (AMU) to analyze VAFB sounding data with the goal of determining the probability of violating (PoV) their upper-level thresholds for wind speed and shear constraints specific to this launch vehicle, and to develop a tool that will calculate the PoV of each constraint on the day of launch. In order to calculate the probability of exceeding each constraint, the AMU collected and analyzed historical data from VAFB. The historical sounding data were retrieved from the National Oceanic and Atmospheric Administration Earth System Research Laboratory archive for the years 1994-2011 and then stratified into four sub-seasons: January-March, April-June, July-September, and October-December. The AMU determined the theoretical distributions that best fit the maximum wind speed and maximum wind shear datasets and applied this information when calculating the averages and standard deviations needed for the historical and real-time PoV calculations. In addition, the AMU included forecast sounding data from the Rapid Refresh model. This information provides further insight for the launch weather officers (LWOs) when determining if a wind constraint violation will occur over the next few hours on the day of launch. The AMU developed an interactive graphical user interface (GUI) in Microsoft Excel using Visual Basic for Applications. The GUI displays the critical sounding data easily and quickly for LWOs on day of launch. This tool will replace the existing one used by the 30 OSSWF, assist the LWOs in determining the probability of exceeding specific wind threshold values, and help to improve the overall upper winds forecast for the launch customer. This presentation will describe how the AMU calculated the historical and real-time PoV values for the specific upper-level wind launch constraints and outline the development of the interactive GUI display.

Shafer, Jaclyn A.↗

Autonomous Real Time Requirements Tracing

One of the more challenging aspects of software development is the ability to verify and validate the functional software requirements dictated by the Software Requirements Specification (SRS) and the Software Detail Design (SDD). Insuring the software has achieved the intended requirements is the responsibility of the Software Quality team and the Software Test team. The utilization of Timeliner-TLX(sup TM) Auto-Procedures for relocating ground operations positions to ISS automated on-board operations has begun the transition that would be required for manned deep space missions with minimal crew requirements. This transition also moves the auto-procedures from the procedure realm into the flight software arena and as such the operational requirements and testing will be more structured and rigorous. The autoprocedures would be required to meet NASA software standards as specified in the Software Safety Standard (NASASTD- 8719), the Software Engineering Requirements (NPR 7150), the Software Assurance Standard (NASA-STD-8739) and also the Human Rating Requirements (NPR-8705). The Autonomous Fluid Transfer System (AFTS) test-bed utilizes the Timeliner-TLX(sup TM) Language for development of autonomous command and control software. The Timeliner- TLX(sup TM) system has the unique feature of providing the current line of the statement in execution during real-time execution of the software. The feature of execution line number internal reporting unlocks the capability of monitoring the execution autonomously by use of a companion Timeliner-TLX(sup TM) sequence as the line number reporting is embedded inside the Timeliner-TLX(sup TM) execution engine. This negates I/O processing of this type data as the line number status of executing sequences is built-in as a function reference. This paper will outline the design and capabilities of the AFTS Autonomous Requirements Tracker, which traces and logs SRS requirements as they are being met during real-time execution of the targeted system. It is envisioned that real time requirements tracing will greatly assist the movement of autoprocedures to flight software enhancing the software assurance of auto-procedures and also their acceptance as reliable commanders

Plattsmier, George I.↗

An Empirical State Error Covariance Matrix Orbit Determination Example

State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. First, consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. Then it follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix of the estimate will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully include all of the errors in the state estimate. The empirical error covariance matrix is determined from a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm. It is a formally correct, empirical state error covariance matrix obtained through use of the average form of the weighted measurement residual variance performance index rather than the usual total weighted residual form. Based on its formulation, this matrix will contain the total uncertainty in the state estimate, regardless as to the source of the uncertainty and whether the source is anticipated or not. It is expected that the empirical error covariance matrix will give a better, statistical representation of the state error in poorly modeled systems or when sensor performance is suspect. In its most straight forward form, the technique only requires supplemental calculations to be added to existing batch estimation algorithms. In the current problem being studied a truth model making use of gravity with spherical, J2 and J4 terms plus a standard exponential type atmosphere with simple diurnal and random walk components is used. The ability of the empirical state error covariance matrix to account for errors is investigated under four scenarios during orbit estimation. These scenarios are: exact modeling under known measurement errors, exact modeling under corrupted measurement errors, inexact modeling under known measurement errors, and inexact modeling under corrupted measurement errors. For this problem a simple analog of a distributed space surveillance network is used. The sensors in this network make only range measurements and with simple normally distributed measurement errors. The sensors are assumed to have full horizon to horizon viewing at any azimuth. For definiteness, an orbit at the approximate altitude and inclination of the International Space Station is used for the study. The comparison analyses of the data involve only total vectors. No investigation of specific orbital elements is undertaken. The total vector analyses will look at the chisquare values of the error in the difference between the estimated state and the true modeled state using both the empirical and theoretical error covariance matrices for each of scenario.

Frisbee, Joseph H., Jr.↗

Hardware in the Loop Testing of an Iodine-Fed Hall Thruster

CUBESATS are relatively new spacecraft platforms that are typically deployed from a launch vehicle as a secondary payload,1 providing low-cost access to space for a wide range of end-users. These satellites are comprised of building blocks having dimensions of 10x10x10 cm cu and a mass of 1.33 kg (a 1-U size). While providing low-cost access to space, a major operational limitation is the lack of a propulsion system that can fit within a CubeSat and is capable of executing high delta v maneuvers. This makes it difficult to use CubeSats on missions requiring certain types of maneuvers (i.e. formation flying, spacecraft rendezvous). Recently, work has been performed investigating the use of iodine as a propellant for Hall-effect thrusters (HETs) 2 that could subsequently be used to provide a high specific impulse path to CubeSat propulsion. Iodine stores as a dense solid at very low pressures, making it acceptable as a propellant on a secondary payload. It has exceptionally high ρIsp (density times specific impulse), making it an enabling technology for small satellite near-term applications and providing the potential for systems-level advantages over mid-term high power electric propulsion options. Iodine flow can also be thermally regulated, subliming at relatively low temperature ( less than100 C) to yield I2 vapor at or below 50 torr. At low power, the measured performance of an iodine-fed HET is very similar to that of a state-of-the-art xenon-fed thruster. Just as importantly, the current-voltage discharge characteristics of low power iodine-fed and xenon-fed thrusters are remarkably similar, potentially reducing development and qualifications costs by making it possible to use an already-qualified xenon-HET PPU in an iodine-fed system. Finally, a cold surface can be installed in a vacuum test chamber on which expended iodine propellant can deposit. In addition, the temperature doesn't have to be extremely cold to maintain a low vapor pressure in the vacuum chamber (it is under 10(exp -6) torr at -75 C), making it possible to 'cryopump' the propellant with lower-cost recirculating refrigerant-based systems as opposed to using liquid nitrogen or low temperature gaseous helium cryopanels. In the present paper, we describe testing performed using an iodine-fed 200 W Hall thruster mounted to a thrust stand and operated in conjunction with MSFCs Small Projects Rapid Integration and Test Environment (SPRITE) Portable Hardware In the Loop (PHIL) hardware. This work is performed in support of the iodine satellite (iSAT) project, which aims to fly a 200-W iodine-fed thruster on a 12-U CubeSat. The SPRITE PHIL hardware allows a given vehicle to do a checkout of its avionics algorithm by allowing it to monitor and feed data to simulated sensors and effectors in a digital environment. These data are then used to determine the attitude of the vehicle and a separate computer is used to interpret the data set and visualize it using a 3D graphical interface. The PHIL hardware allows the testing of the vehicles bus by providing 'real' hardware interfaces (in the case of this test a real RS422 bus) and specific components can be modeled to show their interactions with the avionics algorithm (e.g. a thruster model). For the iSAT project the PHIL is used to visualize the operating cycle of the thruster and the subsequent effect this thrusting has on the attitude of the satellite over a given period of time. The test is controlled using software running on an Andrews Space Cortex 160 flight computer. This computer is the current baseline for a full iSAT mission. While the test could be conducted with a lab computer and software, the team chose to exercise the propulsion system with a representative CubeSat-class computer. For purposes of this test, the "flight" software monitored the propulsion and PPU systems, controlled operation of the thruster, and provided thruster state data to the PHIL simulation. Commands to operate the thruster were initiated from an operator's workstation outside the vacuum chamber and passed through the Cortex 160 to exercise portions of the flight avionics. Two custom-designed pieces of electronics hardware have been designed to operate the propellant feed system. One piece of hardware is an auxiliary board that controls a latch valve, proportional flow control valves (PFCVs) and valve heaters as well as measuring pressures, temperatures and PFCV feedback voltage. An onboard FPGA provides a serial link for issuing commands and manages all lower level input-output functions. The other piece of hardware is a power distribution board, which accepts a standard bus voltage input and converts this voltage into all the different current-voltage types required to operate the auxiliary board. These electronics boards are located in the vacuum chamber near the thruster, exposing this hardware to both the vacuum and plasma environments they would encounter during a mission, with these components communicating to the flight computer through an RS-422 interface. The auxiliary board FPGA provides a 28V MOSFET switch circuit with a 20ms pulse to open or close the iodine propellant feed system latch valve. The FPGA provides a pulse width modulation (PWM) signal to a DC/DC boost converter to produce the 12-120V needed for control of the proportional flow control valve. There are eight MOSFET-switched heating circuits in the system. Heaters are 28V and located in the latch valve, PFCV, propellant tank and propellant feed lines. Both the latch valve and PFCV have thermistors built into them for temperature monitoring. There are also seven resistance temperature device (RTD) circuits on the auxiliary board that can be used to measure the propellant tank and feedline temperatures. The signals are conditioned and sent to an analog to digital converter (ADC), which is directly commanded and controlled by the FPGA.

Polzin, Kurt A.↗