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NASA NTRS1989

A planning and scheduling lexicon

A lexicon related to mission planning and scheduling for spacecraft is presented. Planning and scheduling work is known as sequencing. Sequencing is a multistage process of merging requests from both the science and engineering arenas to accomplish the objectives defined in the requests. The multistage process begins with the creation of science and engineering goals, continues through their integration into the sequence, and eventually concludes with command execution onboard the spacecraft. The objective of this publication is to introduce some formalism into the field of spacecraft sequencing-system technology. This formalism will make it possible for researchers and potential customers to communicate about system requirements and capabilities in a common language.

Cruz, Jennifer W.↗

NASA NTRS1991

Digital Signal Conditioning for Flight Test Instrumentation

This volume in the AGARD Flight Instrumentation Series provides flight test instrumentation engineers with an introduction to digital measurement processes on aircraft. Flight test instrumentation systems are rapidly evolving from analog-intensive to digital-intensive systems, including the use of onboard digital computers. Topics include measurements that are digital in origin, as well as sampling, encoding, transmitting, and storing of data. Particular emphasis is placed on modern avionic data bus architectures and what to be aware of when extracting data from them. Examples of data extraction techniques are given. Tradeoffs between digital logic families, trends in digital development, and design testing techniques are discussed. An introduction to digital filtering is also covered.

Data acquisition↗

NASA NTRS2005

Lessons Learned in the Livingstone 2 on Earth Observing One Flight Experiment

The Livingstone 2 (L2) model-based diagnosis software is a reusable diagnostic tool for monitoring complex systems. In 2004, L2 was integrated with the JPL Autonomous Sciencecraft Experiment (ASE) and deployed on-board Goddard's Earth Observing One (EO-1) remote sensing satellite, to monitor and diagnose the EO-1 space science instruments and imaging sequence. This paper reports on lessons learned from this flight experiment. The goals for this experiment, including validation of minimum success criteria and of a series of diagnostic scenarios, have all been successfully net. Long-term operations in space are on-going, as a test of the maturity of the system, with L2 performance remaining flawless. L2 has demonstrated the ability to track the state of the system during nominal operations, detect simulated abnormalities in operations and isolate failures to their root cause fault. Specific advances demonstrated include diagnosis of ambiguity groups rather than a single fault candidate; hypothesis revision given new sensor evidence about the state of the system; and the capability to check for faults in a dynamic system without having to wait until the system is quiescent. The major benefits of this advanced health management technology are to increase mission duration and reliability through intelligent fault protection, and robust autonomous operations with reduced dependency on supervisory operations from Earth. The work-load for operators will be reduced by telemetry of processed state-of-health information rather than raw data. The long-term vision is that of making diagnosis available to the onboard planner or executive, allowing autonomy software to re-plan in order to work around known component failures. For a system that is expected to evolve substantially over its lifetime, as for the International Space Station, the model-based approach has definite advantages over rule-based expert systems and limit-checking fault protection systems, as these do not scale well. The model-based approach facilitates reuse of the L2 diagnostic software; only the model of the system to be diagnosed and telemetry monitoring software has to be rebuilt for a new system or expanded for a growing system. The hierarchical L2 model supports modularity and expendability, and as such is suitable solution for integrated system health management as envisioned for systems-of-systems.

Hayden, Sandra C.↗

NASA NTRS2007

Generating a Long-Term Land Data Record from the AVHRR and MODIS Instruments

The goal of NASA's Land Long Term Iiata Record (LTDR) project is to produce a consistent long term data set from the AVHRR and MODIS instruments for land climate studies. The project will create daily surface reflectance and normalized difference vegetation index (NDVI) products at a resolution of 0.05 deg., which is identical to the Climate Modeling Grid (CMG) used for MODIS products from EOS Terra and Aqua. Higher order products such as burned area, land surface temperature, albedo, bidirectional reflectance distribution function (BRDF) correction, leaf area index (LAI), and fraction of photosyntheticalIy active radiation absorbed by vegetation (fPAR), will be created. The LTDR project will reprocess Global Area Coverage (GAC) data from AVHRR sensors onboard NOAA satellites by applying the preprocessing improvements identified in the AVHRR Pathfinder Il project and atmospheric and BRDF corrections used in MODIS processing. The preprocessing improvements include radiometric in-flight vicarious calibration for the visible and near infrared channels and inverse navigation to relate an Earth location to each sensor instantaneous field of view (IFOV). Atmospheric corrections for Rayleigh scattering, ozone, and water vapor are undertaken, with aerosol correction being implemented. The LTDR also produces a surface reflectance product for channel 3 (3.75 micrometers). Quality assessment (QA) is an integral part of the LTDR production system, which is monitoring temporal trands in the AVHRR products using time-series approaches developed for MODIS land product quality assessment. The land surface reflectance products have been evaluated at AERONET sites. The AVHRR data record from LTDR is also being compared to products from the PAL (Pathfinder AVHRR Land) and GIMMS (Global Inventory Modeling and Mapping Studies) systems to assess the relative merits of this reprocessing vis-a-vis these existing data products. The LTDR products and associated information can be found at http://ltdr.nascom.nasa.gov/ltdr/ltdr.html.

Pedelty, Jeffrey↗

NASA NTRS2008

Sensor Selection and Data Validation for Reliable Integrated System Health Management

For new access to space systems with challenging mission requirements, effective implementation of integrated system health management (ISHM) must be available early in the program to support the design of systems that are safe, reliable, highly autonomous. Early ISHM availability is also needed to promote design for affordable operations; increased knowledge of functional health provided by ISHM supports construction of more efficient operations infrastructure. Lack of early ISHM inclusion in the system design process could result in retrofitting health management systems to augment and expand operational and safety requirements; thereby increasing program cost and risk due to increased instrumentation and computational complexity. Having the right sensors generating the required data to perform condition assessment, such as fault detection and isolation, with a high degree of confidence is critical to reliable operation of ISHM. Also, the data being generated by the sensors needs to be qualified to ensure that the assessments made by the ISHM is not based on faulty data. NASA Glenn Research Center has been developing technologies for sensor selection and data validation as part of the FDDR (Fault Detection, Diagnosis, and Response) element of the Upper Stage project of the Ares 1 launch vehicle development. This presentation will provide an overview of the GRC approach to sensor selection and data quality validation and will present recent results from applications that are representative of the complexity of propulsion systems for access to space vehicles. A brief overview of the sensor selection and data quality validation approaches is provided below. The NASA GRC developed Systematic Sensor Selection Strategy (S4) is a model-based procedure for systematically and quantitatively selecting an optimal sensor suite to provide overall health assessment of a host system. S4 can be logically partitioned into three major subdivisions: the knowledge base, the down-select iteration, and the final selection analysis. The knowledge base required for productive use of S4 consists of system design information and heritage experience together with a focus on components with health implications. The sensor suite down-selection is an iterative process for identifying a group of sensors that provide good fault detection and isolation for targeted fault scenarios. In the final selection analysis, a statistical evaluation algorithm provides the final robustness test for each down-selected sensor suite. NASA GRC has developed an approach to sensor data qualification that applies empirical relationships, threshold detection techniques, and Bayesian belief theory to a network of sensors related by physics (i.e., analytical redundancy) in order to identify the failure of a given sensor within the network. This data quality validation approach extends the state-of-the-art, from red-lines and reasonableness checks that flag a sensor after it fails, to include analytical redundancy-based methods that can identify a sensor in the process of failing. The focus of this effort is on understanding the proper application of analytical redundancy-based data qualification methods for onboard use in monitoring Upper Stage sensors.

Garg, Sanjay↗

NASA NTRS2008

Post-Flight Estimation of Motion of Space Structures: Part 1

A computer program estimates the relative positions and orientations of two space structures from data on the angular positions and distances of fiducial objects on one structure as measured by a target tracking electronic camera and laser range finders on another structure. The program is written specifically for determining the relative alignments of two antennas, connected by a long truss, deployed in outer space from a space shuttle. The program is based partly on transformations among the various coordinate systems involved in the measurements and on a nonlinear mathematical model of vibrations of the truss. The program implements a Kalman filter that blends the measurement data with data from the model. Using time series of measurement data from the tracking camera and range finders, the program generates time series of data on the relative position and orientation of the antennas. A similar program described in a prior NASA Tech Briefs article was used onboard for monitoring the structures during flight. The present program is more precise and designed for use on Earth in post-flight processing of the measurement data to enable correction, for antenna motions, of scientific data acquired by use of the antennas.

Brugarolas, Paul↗

NASA NTRS2009

Progressive Classification Using Support Vector Machines

An algorithm for progressive classification of data, analogous to progressive rendering of images, makes it possible to compromise between speed and accuracy. This algorithm uses support vector machines (SVMs) to classify data. An SVM is a machine learning algorithm that builds a mathematical model of the desired classification concept by identifying the critical data points, called support vectors. Coarse approximations to the concept require only a few support vectors, while precise, highly accurate models require far more support vectors. Once the model has been constructed, the SVM can be applied to new observations. The cost of classifying a new observation is proportional to the number of support vectors in the model. When computational resources are limited, an SVM of the appropriate complexity can be produced. However, if the constraints are not known when the model is constructed, or if they can change over time, a method for adaptively responding to the current resource constraints is required. This capability is particularly relevant for spacecraft (or any other real-time systems) that perform onboard data analysis. The new algorithm enables the fast, interactive application of an SVM classifier to a new set of data. The classification process achieved by this algorithm is characterized as progressive because a coarse approximation to the true classification is generated rapidly and thereafter iteratively refined. The algorithm uses two SVMs: (1) a fast, approximate one and (2) slow, highly accurate one. New data are initially classified by the fast SVM, producing a baseline approximate classification. For each classified data point, the algorithm calculates a confidence index that indicates the likelihood that it was classified correctly in the first pass. Next, the data points are sorted by their confidence indices and progressively reclassified by the slower, more accurate SVM, starting with the items most likely to be incorrectly classified. The user can halt this reclassification process at any point, thereby obtaining the best possible result for a given amount of computation time. Alternatively, the results can be displayed as they are generated, providing the user with real-time feedback about the current accuracy of classification.

Wagstaff, Kiri↗

NASA NTRS2012

The Organic Aerosols of Titan's Atmosphere

One of Titan's many characteristics is the presence of a haze that veils its surface. This haze is composed of heavy organic particles and determining the chemical composition of these particles is a primary objective for future probes that would conduct in situ analysis. Meanwhile, solar occultations provide constraints on the optical characteristics of the haze layer. This paper describes solar occultation observations obtained by the Visual and Infrared Mapping Spectrometer (VIMS) onboard the Cassini spacecraft. These observations strongly constrain the optical characteristics of the haze layer. We detail the different steps involved in the processing of these data and apply them to two occultations that were observed at the South Pole and at the equator in order to investigate the latitudinal dependence of optical properties. The light curves obtained in seven atmospheric windows between 0.933-microns to 5-microns allow us to characterize atmospheric layers from 300 km to the surface. Very good fits of the light curves are obtained using a simple profile of number density of aerosols that is characterized by a scale height. The main difference between the South Pole and the equator is that the value of the scale height increases with altitude at the South Pole whereas it decreases at the equator. The vertically integrated amount of aerosols is similar at the two locations. The curve describing the cross-section versus wavelength is identical at the two locations suggesting that the aerosols have similar characteristics. Finally, we find that the two-way vertical transmission at 5-microns is as large as 80% at both locations.

solar occultation↗

NASA NTRSDate not supplied

Evaluation of Low-Energy Hydrogen Separation Method Using Metal-Organic Frameworks (MOFs) for Closed-Loop ECLSS Air Revitalization (CLEAR)

The State-of-the-Art (SOA) air revitalization architecture onboard the International Space Station (ISS) recovered approximately 50% of the oxygen (O 2 ) from metabolic carbon dioxide (CO 2 ) via the Sabatier process from 2011 to 2017. O 2 recovery is currently constrained by the limited availability of reactant hydrogen (H 2 ) preventing complete conversion of CO 2 to H 2 O. Increasing O 2 recovery within Closed-Loop ECLSS is essential to reducing resupply mass for long-duration manned missions; specifically focusing on water (H 2 O) which supplies H 2 for Sabatier via water electrolysis. Past ground test endeavors at Marshall Space Flight Center (MSFC) have attempted to recover H 2 from Sabatier-produced CH 4 using technologies such as carbon vapor deposition (CVD) and plasma pyrolysis. The byproducts of these technologies can act as a catalyst poison or reactor deadload to the Sabatier reactor. Hydrogen separation techniques must be utilized to maintain the Sabatier catalyst during gas recycling and must be scalable, non-energy intensive, and safe to operate in a habitation setting. Research indicated that metal-organic frameworks (MOFs) could meet these criteria and were tested for their capability to capture the various carbon-based gaseous products of CVD and plasma pyrolysis such as acetylene (C 2 H 2 ), ethylene (C 2 H 4 ), ethane (C 2 H 6 ), and carbon monoxide (CO) which would purify the hydrogen gas stream passing through the MOF. A sub-scale adsorption column was developed by Marshall Space Flight Center to test three MOF candidates against a synthetic gas mixture comprised of process-relevant carbonous gases and hydrogen to evaluate the separation capability of the MOFs. The results of the hydrogen separation capability, isothermal desorption capability, and demonstrated cyclic reuse of the MOF are presented in this paper.

Kagen Crawford↗

DOE OSTI2020

Investigating Mercury’s Environment with the Two-Spacecraft BepiColombo Mission

The ESA-JAXA BepiColombo mission will provide simultaneous measurements from two spacecraft, offering an unprecedented opportunity to investigate magnetospheric and exospheric dynamics at Mercury as well as their interactions with the solar wind, radiation, and interplanetary dust. Many scientific instruments onboard the two spacecraft will be completely, or partially devoted to study the near-space environment of Mercury as well as the complex processes that govern it. Many issues remain unsolved even after the MESSENGER mission that ended in 2015. The specific orbits of the two spacecraft, MPO and Mio, and the comprehensive scientific payload allow a wider range of scientific questions to be addressed than those that could be achieved by the individual instruments acting alone, or by previous missions. These joint observations are of key importance because many phenomena in Mercury’s environment are highly temporally and spatially variable. Finally, examples of possible coordinated observations are described in this article, analysing the required geometrical conditions, pointing, resolutions and operation timing of different BepiColombo instruments sensors.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1972

Comparison of two sensors for outer planet mission onboard navigation.

Onboard instruments have been shown to be an effective aid to navigation on missions to the outer planets. The relationship of two possible candidate navigation instruments, an image tube (television) and a scanning photometer, with other systems such as data processing and attitude control is discussed. Certain key problem areas relating to the design of each sensor are considered, and the scientific uses of each sensor are examined. The navigational efficacy of both instruments is illustrated by some selected results from a navigation and guidance simulation of outer planet missions. It is concluded that both devices are viable alternatives for onboard outer planet navigation.

Malchow, H. L.↗

NASA NTRS1973

A generalized technique for using cones and dihedral angles in attitude determination, revision 1

Analytic development is presented for a general least squares attitude determination subroutine applicable to spinning satellites. The method is founded on a geometric approach which is completely divorced from considerations relating to particular types and configurations of onboard attitude sensors. Any mix of sensor measurements which can be first transformed (outside the program) to cone or dihedral angle data can be processed. A cone angle is an angle between the spin axis and a known direction line in space; a dihedral angle is an angle between two planes formed by the spin axis and each of two known direction lines. Many different kinds of sensor data can be transformed to these angles, which in turn constitute the actual program inputs, so that the subroutine can be applied without change to a variety of satellite missions. Either a constant or dynamic spin axis model can be handled. The program is also capable of solving for fixed biases in the input angles, in addition to the spin axis attitude solution.

Werking, R. D.↗

NASA NTRS1986

Upper-tropospheric and lower-stratospheric dynamics associated with tropical cyclones as inferred from total ozone measurements

Total ozone associated with western Atlantic and Pacific tropical cyclones at different developmental stages is analyzed in an attempt to monitor the lower-stratospheric and upper-tropospheric mass adjustment processes associated with the tropical cyclone and its environment. The analysis is based on total ozone measurements obtained using the total ozone mapping spectrometer onboard the Nimbus-7. In order to study the total ozone within and surrounding the tropical cyclone, the storm is divided into four regions: the environment, the moat, the central dense overcast, and the eye. Tropical Cyclone Allen is used to discuss the total ozone features that are typical of other western Atlantic and Pacific storms. Western Pacific storms are emphasized in the discussion of the eye total ozone distribution.

Rodgers, Edward↗

NASA NTRS2000

Science Application Teams

This paper discusses the science application team activities. Science Application team are: (1) Represent the diversity of NASA onboard computing of the future. (2) Drive architecture and system software requirements. (3) Demonstrate the benefit of highly capable computing onboard. (4) Study the birth of the first galaxies. (5) Study formation of stars. (6) Discusses the next generation space telescope hardware/software requirement: image processing and on-board optical calibration. Also discusses gamma ray large area space telescope; orbital thermal imaging spectrometer; solar terrestrial probe program; autonomous Mars rover;fault tolerance and errors.

Source record↗

NASA NTRS2005

In-situ exploration of Venus on a global scale : direct measurements of origins and evolution, meterology, dynamics, and chemistry by a long-duration aerial science station

Drifting in the strong winds of Venus under benign Earth-like temperature and pressure conditions, an instrumented balloon-borne science station presents a viable means to explore, in-situ, the Venusian atmosphere on a global scale. Flying over the ground at speeds exceeding 240 km/hour while floating in the Venusian skies near 55 km altitude for several weeks, such an aerostat can conduct a 'world tour' of our neighboring planet, as it circumnavigates the globe multiple times during its flight from equatorial to polar latitudes. Onboard science sensors can repeatedly and directly sample gas compositions, atmospheric pressures and temperatures and cloud particle properties, giving unprecedented insight into the chemical processes occurring within the sulfuric clouds. Additionally, interferometric tracking via Earth-based radio observatories can yield positions and windspeeds to better than 10 cm/sec over one-hour periods, providing important information for understanding the planet's meridional circulation and enigmatic zonal super-rotation, as well as local dynamics associated with meteorological processes. As well, hundreds of GCMS spectra collected during the flight can provide measurements of noble gas compositions and their isotopes with unprecedented accuracy, thereby enabling fundamental new insights into Venus's origin and evolution.

Venus↗

NASA NTRS2011

Virtual Sensor Test Instrumentation

Virtual Sensor Test Instrumentation is based on the concept of smart sensor technology for testing with intelligence needed to perform sell-diagnosis of health, and to participate in a hierarchy of health determination at sensor, process, and system levels. A virtual sensor test instrumentation consists of five elements: (1) a common sensor interface, (2) microprocessor, (3) wireless interface, (4) signal conditioning and ADC/DAC (analog-to-digital conversion/ digital-to-analog conversion), and (5) onboard EEPROM (electrically erasable programmable read-only memory) for metadata storage and executable software to create powerful, scalable, reconfigurable, and reliable embedded and distributed test instruments. In order to maximize the efficient data conversion through the smart sensor node, plug-and-play functionality is required to interface with traditional sensors to enhance their identity and capabilities for data processing and communications. Virtual sensor test instrumentation can be accessible wirelessly via a Network Capable Application Processor (NCAP) or a Smart Transducer Interlace Module (STIM) that may be managed under real-time rule engines for mission-critical applications. The transducer senses the physical quantity being measured and converts it into an electrical signal. The signal is fed to an A/D converter, and is ready for use by the processor to execute functional transformation based on the sensor characteristics stored in a Transducer Electronic Data Sheet (TEDS). Virtual sensor test instrumentation is built upon an open-system architecture with standardized protocol modules/stacks to interface with industry standards and commonly used software. One major benefit for deploying the virtual sensor test instrumentation is the ability, through a plug-and-play common interface, to convert raw sensor data in either analog or digital form, to an IEEE 1451 standard-based smart sensor, which has instructions to program sensors for a wide variety of functions. The sensor data is processed in a distributed fashion across the network, providing a large pool of resources in real time to meet stringent latency requirements.

Wang, Roy↗

NASA NTRS2020

Investigating Mercury's Environment with the Two-Spacecraft BepiColombo Mission

The ESA-JAXA BepiColombo mission will provide simultaneous measurements from two spacecraft, offering an unprecedented opportunity to investigate magnetospheric and exospheric dynamics at Mercury as well as their interactions with the solar wind, radiation, and interplanetary dust. Many scientific instruments onboard the two spacecraft will be completely, or partially devoted to study the near-space environment of Mercury as well as the complex processes that govern it. Many issues remain unsolved even after the MES-SENGER mission that ended in 2015. The specific orbits of the two spacecraft, MPO and Mio, and the comprehensive scientific payload allow a wider range of scientific questions to be addressed than those that could be achieved by the individual instruments acting alone, or by previous missions. These joint observations are of key importance because many phenomena in Mercury’s environment are highly temporally and spatially variable. Examples of possible coordinated observations are described in this article, analysing the required geometrical conditions, pointing, resolutions and operation timing of different BepiColombo instruments sensors.

Mercury's environment↗

NASA NTRS2020

Investigating Mercury’s environment with the Two-Spacecraft BepiColombo Mission

The ESA-JAXA BepiColombo mission will provide simultaneous measurements from two spacecraft, offering an unprecedented opportunity to investigate magnetosphericand exospheric dynamics at Mercury as well as their interactions with the solar wind, radiation, and interplanetary dust. Many scientific instruments onboard the two spacecraft will be completely, or partially devoted to study the near-space environment of Mercury as well as the complex processes that govern it. Many issues remain unsolved even after the MESSENGER mission that ended in 2015. The specific orbits of the two spacecraft, MPO and Mio, and the comprehensive scientific payload allow a wider range of scientific questions to be addressed than those that could be achieved by the individual instruments acting alone, or by previous missions. These joint observations are of key importance because many phenomena in Mercury’s environment are highly temporally and spatially variable. Examples of possible coordinated observations are described in this article, analysing the required geometrical conditions, pointing, resolutions and operation timing of different BepiColombo instruments sensors.

A Milillo↗