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NASA NTRS1993

The systems engineering overview and process (from the Systems Engineering Management Guide, 1990)

The past several decades have seen the rise of large, highly interactive systems that are on the forward edge of technology. As a result of this growth and the increased usage of digital systems (computers and software), the concept of systems engineering has gained increasing attention. Some of this attention is no doubt due to large program failures which possibly could have been avoided, or at least mitigated, through the use of systems engineering principles. The complexity of modern day weapon systems requires conscious application of systems engineering concepts to ensure producible, operable and supportable systems that satisfy mission requirements. Although many authors have traced the roots of systems engineering to earlier dates, the initial formalization of the systems engineering process for military development began to surface in the mid-1950s on the ballistic missile programs. These early ballistic missile development programs marked the emergence of engineering discipline 'specialists' which has since continued to grow. Each of these specialties not only has a need to take data from the overall development process, but also to supply data, in the form of requirements and analysis results, to the process. A number of technical instructions, military standards and specifications, and manuals were developed as a result of these development programs. In particular, MILSTD-499 was issued in 1969 to assist both government and contractor personnel in defining the systems engineering effort in support of defense acquisition programs. This standard was updated to MIL-STD499A in 1974, and formed the foundation for current application of systems engineering principles to military development programs.

Source record↗

NASA NTRS1998

GSFC Cutting Edge Avionics Technologies for Spacecraft

With the launch of NASA's first fiber optic bus on SAMPEX in 1992, GSFC has ushered in an era of new technology development and insertion into flight programs. Predating such programs the Lewis and Clark missions and the New Millenium Program, GSFC has spearheaded the drive to use cutting edge technologies on spacecraft for three reasons: to enable next generation Space and Earth Science, to shorten spacecraft development schedules, and to reduce the cost of NASA missions. The technologies developed have addressed three focus areas: standard interface components, high performance processing, and high-density packaging techniques enabling lower cost systems. To realize the benefits of standard interface components GSFC has developed and utilized radiation hardened/tolerant devices such as PCI target ASICs, Parallel Fiber Optic Data Bus terminals, MIL-STD-1773 and AS1773 transceivers, and Essential Services Node. High performance processing has been the focus of the Mongoose I and Mongoose V rad-hard 32-bit processor programs as well as the SMEX-Lite Computation Hub. High-density packaging techniques have resulted in 3-D stack DRAM packages and Chip-On-Board processes. Lower cost systems have been demonstrated by judiciously using all of our technology developments to enable "plug and play" scalable architectures. The paper will present a survey of development and insertion experiences for the above technologies, as well as future plans to enable more "better, faster, cheaper" spacecraft. Details of ongoing GSFC programs such as Ultra-Low Power electronics, Rad-Hard FPGAs, PCI master ASICs, and Next Generation Mongoose processors.

Luers, Philip J.↗

NASA NTRS2019

GeneLab: Overview of Challenges and Opportunities

Galazka, Jonathan M.↗

NASA NTRS2019

GeneLab: Open Science for Life in Space

Galazka, Jonathan M.↗

NASA NTRSDate not supplied

GeneLab: The NASA Systems Biology Platform for Space Omics Repository, Analysis and Visualization

The NASA GeneLab project capitalizes on multi-omic technologies to maximize the return on spaceflight experiments. To do this, GeneLab maintains a publicly accessible database (GLDS) that houses spaceflight and spaceflight relevant multi-omics data, and collaborates with NASA principal investigators and projects to generate additional omics data. GeneLab houses more than 220 transcriptomic, proteomic, metabolomic and epigenomic datasets from plant, animal and microbial experiments, with a growing number of these having been produced by the GeneLab sample processing lab. The GLDS contains rich metadata about each experiment and has recently integrated radiation dosimetery data from experiments flown on the Space Shuttle. GeneLab has also recently implemented an effort to present processed data in the GLDS in addition to the raw omics data. The processed data will enable interpretation of the data by a larger group of students, scientists and the general public. Standard pipelines for the transformation of raw data into visualizations were developed by four GeneLab Analysis Working Groups (animals, plants, microbes, multi-omics) comprised of over 120 scientists from NASA, industry, and academia. To explore the data, the GLDS provides users various tools for data analysis, collaborative workspace for file storage and sharing, and a visualization portal. The analysis platform built using the Galaxy toolshed provides access to a broad variety of users including those with limited bioinformatics experience and students to learn how to analyze spaceflight omics data. The visualization portal takes GeneLab one step closer to data democratization by removing all bioinformatics requisites to interpret transcriptomics data hosted in the repository. Discoveries made using GeneLab have begun and will continue to deepen our understanding of biology, advance the field of genomics, and help to discover cures for diseases, create better diagnostic tools, and ultimately allow astronauts to better withstand the rigors of long-duration spaceflight.

Samrawit Gebre↗

NASA NTRSDate not supplied

WEBINAR, May 6: New Discoveries Using GeneLab

The NASA GeneLab project capitalizes on multi-omic technologies to maximize the return on spaceflight experiments. To do this, GeneLab maintains a publicly accessible database (GLDS) that houses spaceflight and spaceflight relevant multi-omics data and collaborates with NASA principal investigators and projects to generate additional omics data. GeneLab houses more than 220 transcriptomic, proteomic, metabolomic and epigenomic datasets from plant, animal and microbial experiments, with a growing number of these having been produced by the GeneLab sample processing lab. The GLDS contains rich metadata about each experiment and has recently integrated radiation dosimetry data from experiments flown on the Space Shuttle. GeneLab has also recently implemented an effort to present processed data in the GLDS in addition to the raw omics data. The processed data will enable interpretation of the data by a larger group of students, scientists and the general public. Standard pipelines for the transformation of raw data into visualizations were developed by four GeneLab Analysis Working Groups (animals, plants, microbes, multi-omics) comprised of over 120 scientists from NASA, industry, and academia. To explore the data, the GLDS provides users various tools for data analysis, collaborative workspace for file storage and sharing, and a visualization portal. The analysis platform built using the Galaxy toolshed provides access to a broad variety of users including those with limited bioinformatics experience and students to learn how to analyze spaceflight omics data. The visualization portal takes GeneLab one step closer to data democratization by removing all bioinformatics requisites to interpret transcriptomics data hosted in the repository. Discoveries made using GeneLab have begun and will continue to deepen our understanding of biology, advance the field of genomics, and help to discover cures for diseases, create better diagnostic tools, and ultimately allow astronauts to better withstand the rigors of long-duration spaceflight.

Sylvain V. Costes↗

NASA NTRS2006

A Multi-mission Event-Driven Component-Based System for Support of Flight Software Development, ATLO, and Operations first used by the Mars Science Laboratory (MSL) Project

This paper details an architectural description of the Mission Data Processing and Control System (MPCS), an event-driven, multi-mission ground data processing components providing uplink, downlink, and data management capabilities which will support the Mars Science Laboratory (MSL) project as its first target mission. MPCS is developed based on a set of small reusable components, implemented in Java, each designed with a specific function and well-defined interfaces. An industry standard messaging bus is used to transfer information among system components. Components generate standard messages which are used to capture system information, as well as triggers to support the event-driven architecture of the system. Event-driven systems are highly desirable for processing high-rate telemetry (science and engineering) data, and for supporting automation for many mission operations processes.

Mission Data Processing and Control System (MPCS)↗

NASA NTRSDate not supplied

Method Development for In-situ Detection of Latent Herpesvirus DNA from Saliva using Nanopore Sequencing

Research toward latent herpesvirus reactivation has been intensively addressed through Space Shuttle and International Space Station (ISS) investigations. This work has provided the understanding that persistent reactivation of herpesviruses from asymptomatic crew can be detected through viral shedding in saliva, urine, and blood. Occasionally, viral reactivation from the latency stage can pose a threat to crew health (clinical manifestation) before, during, and after flight missions. Furthermore, previous work detailing correlations with immunity indicate that monitoring viral reactivation could be implemented to assess potential immune dysfunction. While in-flight monitoring is desirable, there is no well-established procedure or method for real-time evaluations, and research to date has relied on postflight, ground-based analysis. The development of portable molecular technologies like the miniPCR™ (miniPCR Bio) thermal cycler and the MinION™ sequencer (Oxford Nanopore Technologies) have confirmed that real-time monitoring is possible in extreme and low resource environments. These devices, combined with simple sample preparation methods, have been used to demonstrate bacterial identification onboard the ISS, as well as rapid viral detection in remote locations on Earth. The work here builds upon previous molecular advancements onboard the ISS toward the development and validation of a spaceflight-compatible method for viral detection from crew samples. Several herpesviruses can be detected in saliva, which provides a non-invasive means to collect samples for monitoring. While the basis for this method lies in previous spaceflight investigations, key points for method optimization include DNA extraction from saliva, viral primer selection, and bioinformatic processes for data analysis. To increase viral yield, numerous DNA extraction methods have been evaluated and will be discussed in detail. For initial development and testing, varicella-zoster virus (VZV) is being targeted though open reading frame 51 and 63 (ORF51, ORF63), as the replication origin-binding protein is highly expressed during latency. Optimization of the thermal cycling parameters has resulted in the ability to test the entire process. The full method has been tested with both viral VZV DNA standards and saliva spiked with varying concentrations of VZV. Viral sequence data were mapped to the reference sequence using minimap2. Prior to mapping, DNA sequencing reads were filtered for length and quality, barcodes were removed, and alignment identity calculated. Following further assessments, statistics were compared across multiple sequencing experiments and are being used to determine the success of the protocols. Forward work will include the incorporation of herpes simplex virus 1 (HSV-1) and Epstein-Barr virus (EBV) primers as well as the validation of results to the terrestrial qPCR standard assay. Upon full validation of the developed method, saliva will be collected from 20 healthy subjects and spiked with viral DNA. These samples will be split and assayed with the MinION and standard qPCR assay.

Hang N Nguyen↗

NASA NTRS2006

An Operational Configuration of the ARPS Data Analysis System to Initialize WRF in the NM'S Environmental Modeling System

The Weather Research and Forecasting (WRF) model is the next generation community mesoscale model designed to enhance collaboration between the research and operational sectors. The NM'S as a whole has begun a transition toward WRF as the mesoscale model of choice to use as a tool in making local forecasts. Currently, both the National Weather Service in Melbourne, FL (NWS MLB) and the Spaceflight Meteorology Group (SMG) are running the Advanced Regional Prediction System (AIRPS) Data Analysis System (ADAS) every 15 minutes over the Florida peninsula to produce high-resolution diagnostics supporting their daily operations. In addition, the NWS MLB and SMG have used ADAS to provide initial conditions for short-range forecasts from the ARPS numerical weather prediction (NWP) model. Both NM'S MLB and SMG have derived great benefit from the maturity of ADAS, and would like to use ADAS for providing initial conditions to WRF. In order to assist in this WRF transition effort, the Applied Meteorology Unit (AMU) was tasked to configure and implement an operational version of WRF that uses output from ADAS for the model initial conditions. Both agencies asked the AMU to develop a framework that allows the ADAS initial conditions to be incorporated into the WRF Environmental Modeling System (EMS) software. Developed by the NM'S Science Operations Officer (S00) Science and Training Resource Center (STRC), the EMS is a complete, full physics, NWP package that incorporates dynamical cores from both the National Center for Atmospheric Research's Advanced Research WRF (ARW) and the National Centers for Environmental Prediction's Non-Hydrostatic Mesoscale Model (NMM) into a single end-to-end forecasting system. The EMS performs nearly all pre- and postprocessing and can be run automatically to obtain external grid data for WRF boundary conditions, run the model, and convert the data into a format that can be readily viewed within the Advanced Weather Interactive Processing System. The EMS has also incorporated the WRF Standard Initialization (SI) graphical user interface (GUT), which allows the user to set up the domain, dynamical core, resolution, etc., with ease. In addition to the SI GUT, the EMS contains a number of configuration files with extensive documentation to help the user select the appropriate input parameters for model physics schemes, integration timesteps, etc. Therefore, because of its streamlined capability, it is quite advantageous to configure ADAS to provide initial condition data to the EMS software. One of the biggest potential benefits of configuring ADAS for ingest into the EMS is that the analyses could be used to initialize either the ARW or NMM. Currently, the ARPS/ADAS software has a conversion routine only for the ARW dynamical core. However, since the NIvIM runs about 2.5 times faster than the ARW, it is quite advantageous to be able to run an ADAS/NMM configuration operationally due to the increased efficiency.

Case, Jonathan↗

NASA NTRSDate not supplied

Elevating the Quality of Space Omics Sequencing Data: Innovations and Methodologies from NASA GeneLab Sample Processing Laboratory

NASA’s GeneLab, part of the NASA Open Science Data Repository, is a space-related database that hosts a diverse range of transcriptomics, proteomics, epigenomics and genomics data. The NASA GeneLab Sample Processing Laboratory (SPL) generates omics data from biological experiments conducted aboard the International Space Station, Space Shuttle and space related ground experiments, this omics data then hosted on the GeneLab repository. Samples generated such experiments pose numerous technical challenges such as small experimental sample size, variance in dissection times, limited tissue preservation methods, prolonged storage time, and more. GeneLab SPL team had developed specialized expertise in nucleic acid extraction, library preparation and sequencing of such biological samples via extensive training and years of experience. In order to ensure data accuracy and consistency across experiments, SPL has developed standardized protocols for each species and tissue type. These protocols in conjunction with quality control metrics and data standards are crucial in generating of high-quality data. SPL protocols and standards have been developed in collaboration with the scientific community and had been made publicly available on the GeneLab portal, guaranteeing comparability of datasets across spaceflight experiments. To ensure reliability of data generation, SPL leverages cutting-edge innovations in laboratory automation for sample processing. By leveraging these state-of-the-art platforms, SPL achieves high levels of data reproducibility while significantly minimizing sources of bias and variability, especially across experiments with large numbers of samples. Over the past few years, the space biology investigator community has accessed SPL-generated data from the Open Science Data Repository for a myriad of data re-analysis and re-use studies. We observe a trend that in-house SPL-generated data consistently outperforms outsourced sequencing data in terms of technical standards, quality control metrics, timeliness of data delivery, and sequencing and reagent efficiency. Superior data generation has and will continue to enable discoveries in disease, diagnostic tools, and the biological effects of long duration spaceflight.

GeneLab↗

NASA NTRS2001

TAXI Direct-to-Disk Interface Demultiplexes Proprietarily Formatted Data

The TAXI Direct-to-Disk interface is a special-purpose interface circuit for demultiplexing of data from a Racal Storeplex (or equivalent) multichannel recorder onto one or more hard disks that reside in, and/or are controlled by, a personal computer (PC). (The name TAXI as used here is derived from the acronym TAXI, which signifies transparent asynchronous transceiver interface.) The TAXI Direct-to-Disk interface was developed for original use in capturing data from instrumentation on a test stand in a NASA rocket-testing facility. The control, data-recording, and data-postprocessing equipment of the facility are located in a control room at a safe distance from the test stand. Heretofore, the transfer of data from the instrumentation to the postprocessing equipment has entailed post-test downloading via software, requiring many hours to days of post-test reduction before the data could be viewed in a channelized format. The installation of the TAXI Direct-to-Disk interface, in conjunction with other modifications, causes the transfer of data to take place in real time, so that the data are immediately available for review during or after the test. The instrumentation is connected to the input terminals of the signal-processing unit of multichannel recorder by standard coaxial cables. The coaxial output of the signal processing unit is converted to fiber-optic output by means of a commercial coaxial-cable/fiber-optic converter (that is, a fiber-optic transceiver) designed specifically for this application. The fiber-optic link carries the data signals to an identical fiber-optic transceiver in the control room. On the way to the TAXI Direct-to-Disk interface that is the focus of this article, the data signals are processed through a companion special purpose circuit denoted by the similar name parallel TAXI interface.

Newnan, Bruce G.↗

NASA NTRS1985

Sea surface temperatures from VAS MSI data

The results of the SST intercomparison workshop series are the first examination of monthly mean SSTs derived from MSI data provided by the VAS instrument on the GOES series satellites. The most significant change in deriving the SST's was the use of the three window channel algorithm in the processing of the July data as opposed to the use of only the two window channel algorithm for the March data. In addition, further satellite/buoy matches indicated that the triple window channel algorithm showed a smaller standard deviation than the two window channel algorithm and was less sensitive to the effects of volcanic aerosol contamination and low level inversion conditions. This is due to the smaller brightness temperature attenuation by aerosols and water vapor at 3.9 microns than at 11.0 and 12.6 microns. Thus, the decision was made to use the best product (i.e., the three window channel aglorithm) for processing the July data.

Bates, J. J.↗

NASA NTRS1993

Space Applications Industrial Laser System (SAILS)

A program is underway to develop a YAG laser based materials processing workstation to fly in the cargo bay of the Space Shuttle. This workstation, called Space Applications Industrial Laser System (SAILS), will be capable of cutting and welding steel, aluminum, and Inconel alloys of the type planned for use in constructing the Space Station Freedom. As well as demonstrating the ability of a YAG laser to perform remote (fiber-optic delivered) repair and fabrication operations in space, fundamental data will be collected on these interactions for comparison with terrestrial data and models. The flight system, scheduled to fly in 1996, will be constructed as three modules using standard Get-Away-Special (GAS) canisters. The first module holds the laser head and cooling system, while the second contains a high peak power electrical supply. The third module houses the materials processing workstation and the command and data acquisition subsystems. The laser head and workstation cansisters are linked by a fiber-optic cable to transmit the laser light. The team assembled to carry out this project includes Lumonics Industrial Products (laser), Tennessee Technological University (structural analysis and fabrication), Auburn University Center for Space Power (electrical engineering), University of Waterloo (low-g laser process consulting), and CSTAR/UTSI (data acquisition, control, software, integration, experiment design). This report describes the SAILS program and highlights recent activities undertaken at CSTAR.

Mccay, T. D.↗

NASA NTRS2008

Measurement Assurance for End-Item Users

The goal of a Quality Management System (QMS) as specified in ISO 9001 and AS9100 is to assure the end product meets specifications and customer requirements. Measuring devices, often called measuring and test equipments (MTE), provide the evidence of product conformity to the prescribed requirements. Therefore the processes which employ MTE can become a weak link to the overall QMS if proper attention is not given to development and execution of these processes. Traditionally, calibration of MTE is given more focus in industry standards and process control efforts than the equally important proper usage of the same equipment. It is a common complaint of calibration laboratory personnel that MTE users are only interested in "a sticker." If the QMS requires the MTE "to demonstrate conformity of the product," then the quality of the measurement process must be adequate for the task. This leads to an ad hoc definition; measurement assurance is a discipline that assures that all processes, activities, environments, standards, and procedures involved in making a measurement produce a result that can be rigorously evaluated for validity and accuracy. To evaluate that the existing measurement processes are providing an adequate level of quality to support the decisions based upon this measurement data, an understanding of measurement assurance basics is essential. This topic is complimentary to the calibration standard, ANSI/NCSL Z540.3-2006, which targets the calibration of MTE at the organizational level. This paper will discuss general measurement assurance when MTE is used to provide evidence of product conformity, therefore the target audience of this paper is end item users of MTE. A central focus of the paper will be the verification of tolerances and the associated risks, so calibration professionals may find the paper useful in communication with their customers, MTE users.

Mimbs, Scott M.↗

NASA NTRS2018

GMI-IPS: Python Processing Software for Aircraft Campaigns

NASA's Atmospheric Tomography Mission (ATom) seeks to understand the impact of anthropogenic air pollution on gases in the Earth's atmosphere. Four flight campaigns are being deployed on a seasonal basis to establish a continuous global-scale data set intended to improve the representation of chemically reactive gases in global atmospheric chemistry models. The Global Modeling Initiative (GMI), is creating chemical transport simulations on a global scale for each of the ATom flight campaigns. To meet the computational demands required to translate the GMI simulation data to grids associated with the flights from the ATom campaigns, the GMI ICARTT Processing Software (GMI-IPS) has been developed and is providing key functionality for data processing and analysis in this ongoing effort. The GMI-IPS is written in Python and provides computational kernels for data interpolation and visualization tasks on GMI simulation data. A key feature of the GMI-IPS, is its ability to read ICARTT files, a text-based file format for airborne instrument data, and extract the required flight information that defines regional and temporal grid parameters associated with an ATom flight. Perhaps most importantly, the GMI-IPS creates ICARTT files containing GMI simulated data, which are used in collaboration with ATom instrument teams and other modeling groups. The initial main task of the GMI-IPS is to interpolate GMI model data to the finer temporal resolution (1-10 seconds) of a given flight. The model data includes basic fields such as temperature and pressure, but the main focus of this effort is to provide species concentrations of chemical gases for ATom flights. The software, which uses parallel computation techniques for data intensive tasks, linearly interpolates each of the model fields to the time resolution of the flight. The temporally interpolated data is then saved to disk, and is used to create additional derived quantities. In order to translate the GMI model data to the spatial grid of the flight path as defined by the pressure, latitude, and longitude points at each flight time record, a weighted average is then calculated from the nearest neighbors in two dimensions (latitude, longitude). Using SciPya's Regular Grid Interpolator, interpolation functions are generated for the GMI model grid and the calculated weighted averages. The flight path points are then extracted from the ATom ICARTT instrument file, and are sent to the multi-dimensional interpolating functions to generate GMI field quantities along the spatial path of the flight. The interpolated field quantities are then written to a ICARTT data file, which is stored for further manipulation. The GMI-IPS is aware of a generic ATom ICARTT header format, containing basic information for all flight campaigns. The GMI-IPS includes logic to edit metadata for the derived field quantities, as well as modify the generic header data such as processing dates and associated instrument files. The ICARTT interpolated data is then appended to the modified header data, and the ICARTT processing is complete for the given flight and ready for collaboration. The output ICARTT data adheres to the ICARTT file format standards V1.1. The visualization component of the GMI-IPS uses Matplotlib extensively and has several functions ranging in complexity. First, it creates a model background curtain for the flight (time versus model eta levels) with the interpolated flight data superimposed on the curtain. Secondly, it creates a time-series plot of the interpolated flight data. Lastly, the visualization component creates averaged 2D model slices (longitude versus latitude) with overlaid flight track circles at key pressure levels. The GMI-IPS consists of a handful of classes and supporting functionality that have been generalized to be compatible with any ICARTT file that adheres to the base class definition. The base class represents a generic ICARTT entry, only defining a single time entry and 3D spatial positioning parameters. Other classes inherit from this base class; several classes for input ICARTT instrument files, which contain the necessary flight positioning information as a basis for data processing, as well as other classes for output ICARTT files, which contain the interpolated model data. Utility classes provide functionality for routine procedures such as: comparing field names among ICARTT files, reading ICARTT entries from a data file and storing them in data structures, and returning a reduced spatial grid based on a collection of ICARTT entries. Although the GMI-IPS is compatible with GMI model data, it can be adapted with reasonable effort for any simulation that creates Hierarchical Data Format (HDF) files. The same can be said of its adaptability to ICARTT files outside of the context of the ATom mission. The GMI-IPS contains just under 30,000 lines of code, eight classes, and a dozen drivers and utility programs. It is maintained with GIT source code management and has been used to deliver processed GMI model data for the ATom campaigns that have taken place to date.

Damon, M. R.↗

NASA NTRS1989

Advanced concepts for telemetry data systems

The Consultative Committee for Space Data Standards (CCSDS) has defined Advanced Orbiting System (AOS) standards for the overall architectural framework of future packet telemetry systems. The standards encompass a CCSDS principal network covering the onboard space-link and ground systems, and furnishes an asynchronous (telemetry/internetworking) and isochronous (audio and video) data-transport services employing CCSDS packets and virtual channels. Attention is given to changes envisioned in ground telemetry processing systems currently in use, as well as to the application of CCSDS standards to future systems.

Pritchard, James A.↗

NASA NTRS1992

LORAN-C data reduction at the US Naval Observatory

As part of its mission and in cooperation with the U.S. Coast Guard, the U.S. Naval Observatory (USNO) monitors and reports the timing of the LORAN-C chains. The procedures for monitoring and processing the reported values have evolved with advances in monitoring equipment, computer interfaces and PCs. This paper discusses the current standardized procedures used by USNO to sort the raw data according to Group Repetition Interval (GRI) rate, to fit and smooth the data points, and, for chains remotely monitored, to tie the values to the USNO Master Clock. The results of these procedures are the LORAN time of transmission values, as references to UTC(USNO) (Universal Coordinated Time) for all LORAN chains. This information is available to users via USNO publications and the USNO Automated Data Service (ADS).

Harold Chadsey↗

NASA NTRS2001

Flight Computer Design for the Space Technology 5 (ST-5) Mission

As part of NASA's New Millennium Program, the Space Technology 5 mission will validate a variety of technologies for nano-satellite and constellation mission applications. Included are: a miniaturized and low power X-band transponder, a constellation communication and navigation transceiver, a cold gas micro-thruster, two different variable emittance (thermal) controllers, flex cables for solar array power collection, autonomous groundbased constellation management tools, and a new CMOS ultra low-power, radiation-tolerant, +0.5 volt logic technology. The ST-5 focus is on small and low-power. A single-processor, multi-function flight computer will implement direct digital and analog interfaces to all of the other spacecraft subsystems and components. There will not be a distributed data system that uses a standardized serial bus such as MIL-STD-1553 or MIL-STD-1773. The flight software running on the single processor will be responsible for all real-time processing associated with: guidance, navigation and control, command and data handling (C&DH) including uplink/downlink, power switching and battery charge management, science data analysis and storage, intra-constellation communications, and housekeeping data collection and logging. As a nanosatellite trail-blazer for future constellations of up to 100 separate space vehicles, ST-5 will demonstrate a compact (single board), low power (5.5 watts) solution to the data acquisition, control, communications, processing and storage requirements that have traditionally required an entire network of separate circuit boards and/or avionics boxes. In addition to the New Millennium technologies, other major spacecraft subsystems include the power system electronics, a lithium-ion battery, triple-junction solar cell arrays, a science-grade magnetometer, a miniature spinning sun sensor, and a propulsion system.

Speer, David↗