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At least 91 records · Page 5

Machine Learning Airport Surface Model

Future needs of the National Airspace System require decision support tools to adopt a service-oriented architecture in alignment with the FAA’s vision for an Info-Centric NAS. To achieve this, many existing systems will need to undergo a digital transformation from a monolithic decision support tool to a service-oriented architecture where individual services are exposed through well defined Application Programming Interfaces (APIs). To enable this transformation, NASA has developed the Digital Information Platform as a cloud based foundation for development of aviation services with a special focus towards Artificial Intelligence and Machine Learning (ML) services. This paper describes the work required for the transformation of NASA’s legacy surface management system to a real-time ML based decision support system deployed in the cloud. Details of the Machine Learning Operations (MLOps) infrastructure and best practices are described which enabled the end-toend lifecycle management of ML within an integrated software system. Validation results are provided from an operational field evaluation where performance was benchmarked against the legacy approach.

Jeremy Coupe↗

A PPE Use Case on Configuration Management Approach for MBSE

Systems engineers worldwide have been working to implement Model-based Systems Engineering (MBSE) environments, tools, and methodologies. MBSE is a formalized application of modeling to support systems engineering, including requirements, design, analysis, verification, and validation activities over the project’s lifecycle[1]; MBSE captures the system data into a digital environment. Significant benefits of MBSE includes a reduction in the time in performing systems engineering activities and an improvement higher fidelity data production. As more Systems Engineers are using MBSE, the models it produces are becoming the source of truth for Systems Engineering artifacts. As we move towards using these models as the source of truth, a more rigorous Configuration Management (CM) infrastructure is needed. Many of the MBSE tools provide CM options but utilizing them efficiently and effectively can be challenging. More rigorous methods and tools are needed to assist with keeping track of changes in the model, making sure inadvertent changes to baseline data did not occur, visibility of changes in the different model versions, and the impacts of changes to the models. System engineers and configuration management personnel from the Power and Propulsion Element (PPE) project at NASA Glenn Research Center have been working to develop a modeling construct that allows models to be the source of truth and maintain a configuration managed baseline. This paper presents a process that leverages the existing CM tools and describes how PPE used this process to manage changes more rigorously. It will describe the process behind building the model architecture that utilizes the MBSE tool capabilities and the configuration management process. It will contain some of the advantages and disadvantages of the architecture that the PPE project had settled upon utilizing, as well as some enhanced capabilities that the PPE MBSE team has developed.

MBSE↗

Software Configurable Multichannel Transceiver

Emerging test instrumentation and test scenarios increasingly require network communication to manage complexity. Adapting wireless communication infrastructure to accommodate challenging testing needs can benefit from reconfigurable radio technology. A fundamental requirement for a software-definable radio system is independence from carrier frequencies, one of the radio components that to date has seen only limited progress toward programmability. This paper overviews an ongoing project to validate the viability of a promising chipset that performs conversion of radio frequency (RF) signals directly into digital data for the wireless receiver and, for the transmitter, converts digital data into RF signals. The Software Configurable Multichannel Transceiver (SCMT) enables four transmitters and four receivers in a single unit the size of a commodity disk drive, programmable for any frequency band between 1 MHz and 6 GHz.

Freudinger, Lawrence C.↗

NASA's Earth Observing Data and Information System - Near-Term Challenges

NASA's Earth Observing System Data and Information System (EOSDIS) has been a central component of the NASA Earth observation program since the 1990's. EOSDIS manages data covering a wide range of Earth science disciplines including cryosphere, land cover change, polar processes, field campaigns, ocean surface, digital elevation, atmosphere dynamics and composition, and inter-disciplinary research, and many others. One of the key components of EOSDIS is a set of twelve discipline-based Distributed Active Archive Centers (DAACs) distributed across the United States. Managed by NASA's Earth Science Data and Information System (ESDIS) Project at Goddard Space Flight Center, these DAACs serve over 3 million users globally. The ESDIS Project provides the infrastructure support for EOSDIS, which includes other components such as the Science Investigator-led Processing systems (SIPS), common metadata and metrics management systems, specialized network systems, standards management, and centralized support for use of commercial cloud capabilities. Given the long-term requirements, and the rapid pace of information technology and changing expectations of the user community, EOSDIS has evolved continually over the past three decades. However, many challenges remain. Challenges addressed in this paper include: growing volume and variety, achieving consistency across a diverse set of data producers, managing information about a large number of datasets, migration to a cloud computing environment, optimizing data discovery and access, incorporating user feedback from a diverse community, keeping metadata updated as data collections grow and age, and ensuring that all the content needed for understanding datasets by future users is identified and preserved.

Remote Sensing↗

Industry Support

NASA Glenn Research Center (GRC) is responsible for the Advanced Communications for Air Traffic Management (AC/ATM) Project, a sub-element task of the Advanced Air Transportation Technologies (AATT) Project of the NASA Aviation System Capacity Program (ASC). The AC/ATM Project is developing new communications technologies and tools that will improve throughput in the U.S. Air Traffic Control System. The goal of the AC/ATM Project is to enable a communications infrastructure providing the capacity, efficiency, and flexibility necessary to realize benefits of the future mature Free-Flight environment. The capabilities and scope of communications technologies needed to accomplish this goal depend on characteristics of the future Free-Flight environment. There are many operational concepts being proposed for a future ATM system to enable user flexibility and efficiency. GRC s focus is on developing new technologies and techniques to support the digital communication of information involving airborne and ground-based users. However, the technologies and techniques must be integrated with the systems and services that industry and the Federal Aviation Administration (FAA) are developing. Thus, GRC needs to monitor and provide input to the various industry and FAA organizations and committees that are specifying new systems and services. Adoption of technologies by the FAA is partially dependent on acceptance of the technology by the aviation community. The commercial aviation community in particular would like to adopt technologies that can be used throughout the world. As a result, the adoption of common or at least compatible technologies by European countries is a key factor in getting commitments to those technologies by the US aviation community. GRC desires to keep informed of European activities that relate to aviation communication technologies, particularly those that are being supported by Eurocontrol.

Source record↗

New Flight Rules to Enable the Era of Aerial Mobility in the National Airspace System

In the 21st Century, new aviation markets, vehicle types, and technologies are fast emerging, inspiring new operational concepts for the National Airspace System such as Unmanned Aircraft Systems Traffic Management and Urban Air Mobility. These novel operations envision a dramatic increase in aerial mobility, or the ability to navigate freely through the airspace with unprecedented access and operational flexibility. Implementing these concepts presents a major challenge to the existing operational modes of Visual Flight Rules (VFR) and Instrument Flight Rules (IFR), developed under the limitations of early 20th Century technology and procedures to ensure safe navigation and separation from traffic. To meet this challenge and to support the needs of operators in the 21st Century and beyond, this paper proposes that VFR and IFR be augmented by new flight rules – Digital Flight Rules (DFR) – that leverage modern and emerging technologies and are not bound by restrictions borne of the state of technology 75-100 years ago. The objective of DFR is to provide safe and unfettered access to the airspace to all participating vehicle operators under all visibility conditions without incurring the limitations in operational flexibility inherent to IFR and even VFR. Advancements in communications, navigation, surveillance, aircraft connectivity, information access, automation technology, and supporting ground infrastructure provide the opportunity for the vehicle operator to engage at an unprecedented level in managing their flights regardless of flight visibility. Under DFR, these advancements enable the vehicle operator to assume full responsibility for traffic separation and therefore full trajectory management authority in all visibility conditions and airspace regions. The changes in roles and responsibilities are expected to enable greater airspace access and operational flexibility than afforded by IFR and VFR, thus enabling the emergence of new operations and a new era of advanced aerial mobility.

Mobility↗

Learning Effectiveness of the NASA Digital Learning Network

Student participation in actual investigations which develop inquiry and intellectual skills has long been regarded as an essential component of science instructions (Schwab, 1962; White, 1999). Such investigations give students an opportunity to appreciate the spirit of science and promote an understanding of the nature of science. However, classroom research conducted over the past 20 years describes science teaching as primarily teacher centered. Typical instruction consists of whole class, noninteractive activities in which individual seatwork has constituted the bulk of classroom interactions (Tobin and Gallagher, 1997). Students typically learn science from textbooks and lectures. Their main motivation is to do reasonably well on tests and examinations (Layman, 1999). During the past five years, infrastructure constraints have reduced to the point that many schools systems can now afford low cost, high quality video conferencing equipment (International Society for Technology in Education, 2003). This study investigates the use of interactive video conferencing vs. face to face interaction with hands-on, inquiry based activities. Some basic questions to be addressed are: How does the delivery method impact the students understanding of the goals of the experiment? Are students explanation of the strategies of experimentation different based on the method of instruction that was provided. Do students engaged in a workshop with the instructor in the room vs. an instructor over video conferencing have different perception of the understanding of the subject materials?

Hix, Billy↗

Satellite Communications for ATM

This presentation is an overview on Satellite Communication for the Aeronautical Telecommunication Management (ATM) research. Satellite Communications are being considered by the FAA and NASA as a possible alternative to the present and future ground systems supporting Air Traffic Communications. The international Civil Aviation Organization (ICAO) have in place Standards and Recommended Practices (SARPS) for the Aeronautical Mobile Satellite Services (AMSS) which is mainly derived from the pre-existing Inmarsat service that has been in service since the 1980s. The Working Group A of the Aeronautical Mobile Communication Panel of ICAO has also been investigating SARPS for what is called the Next Generation Satellite Service (NGSS) which conforms less to the Inmarsat based architecture and explores wider options in terms of satellite architectures. Several designs are being proposed by Firms such as Boeing, ESA, NASA that are geared toward full or secondary usage of satellite communications for ATM. Satellite communications for ATM can serve several purposes ranging from primary usage where ground services would play a minimal backup role, to an integrated solution where it will be used to cover services, or areas that are less likely to be supported by the proposed and existing ground infrastructure. Such Integrated roles can include usage of satellite communications for oceanic and remote land areas for example. It also can include relieving the capacity of the ground network by providing broadcast based services of Traffic Information Services messages (TIS-B), or Flight Information Services (FIS-B) which can take a significant portion of the ground system capacity. Additionally, satellite communication can play a backup role to support any needs for ground replacement, or additional needed capacity even after the new digital systems are in place. The additional bandwidth that can be provided via satellite communications can also open the door for many new applications that generally will enhance the standard services provided. All of those possibilities were investigated and comments, as well as descriptions of those analyses are put forward, as well as suggestions for future areas of study.

Shamma, Mohammed A.↗

ExMC Digital Engineering

Future missions beyond Artemis II will become increasingly complex as multiple vehicles (e.g., Gateway, Human Landing System (HLS), and Extravehicular Activity and Human Surface Mobility Program (EHP)), each having their own Program requirements and other associated documentation, which will need to be integrated into a single mission. Currently, the Human Health and Performance Directorate (HHPD)Program Support Teams mostly use documents to manage, perform, and archive their analyses. Identifying an opportunity for efficiency, ExMC demonstrated the ability to utilize MagicDraw, a Model-Based Systems Engineering (MBSE) tool, as a requirements database with traceability, dependencies, and relationships in one place. Rather than existing in documents, emails, and historical knowledge, ExMC pursued a Digital Engineering (DE) effort in coordination with HHPD by combining MBSE tools with other digital platforms to manage and develop user-defined databases and interfaces. This DE approach is aimed to simplify processes and reduce risk through the unification of requirements into a centralized digital network, improving collaboration, decision-making, and transparency compared to isolated documents and knowledge. However, manipulating data views and content in MagicDraw requires a steep learning curve not needed by all users and even the user-friendly web view comes with downsides due to the static views. To provide a more dynamic user interface, ExMC investigated the use of Microsoft Power Platform which does not require as steep of a learning curve to become proficient. This introduces analytics to the DE infrastructure, offering customizable and dynamic data dashboards. ExMC continues developing these dashboards and tailoring the DE infrastructure in alignment with HHPD workforce needs.

M Krihak↗

Human Exploration Spacecraft Testbed for Integration and Advancement (HESTIA)

The proposed paper will cover ongoing effort named HESTIA (Human Exploration Spacecraft Testbed for Integration and Advancement), led at the National Aeronautics and Space Administration (NASA) Johnson Space Center (JSC) to promote a cross-subsystem approach to developing Mars-enabling technologies with the ultimate goal of integrated system optimization. HESTIA also aims to develop the infrastructure required to rapidly test these highly integrated systems at a low cost. The initial focus is on the common fluids architecture required to enable human exploration of mars, specifically between life support and in-situ resource utilization (ISRU) subsystems. An overview of the advancements in both integrated technologies, in infrastructure, in simulation, and in modeling capabilities will be presented, as well as the results and findings of integrated testing,. Due to the enormous mass gear-ratio required for human exploration beyond low-earth orbit, (for every 1 kg of payload landed on Mars, 226 kg will be required on Earth), minimization of surface hardware and commodities is paramount. Hardware requirements can be minimized by reduction of equipment performing similar functions though for different subsystems. If hardware could be developed which meets the requirements of both life support and ISRU it could result in the reduction of primary hardware and/or reduction in spares. Minimization of commodities to the surface of mars can be achieved through the creation of higher efficiency systems producing little to no undesired waste, such as a closed-loop life support subsystem. Where complete efficiency is impossible or impractical, makeup commodities could be manufactured via ISRU. Although, utilization of ISRU products (oxygen and water) for crew consumption holds great promise of reducing demands on life support hardware, there exist concerns as to the purity and transportation of commodities. To date, ISRU has been focused on production rates and purities for propulsion needs. The meshing of requirements between all potential users, producers, and cleaners of oxygen and water is crucial to guiding the development of technologies which will be used to perform these functions. Various new capabilities are being developed as part of HESTIA, which will enable the integrated testing of these technologies. This includes the upgrading of a 20' diameter habitat chamber to eventually support long duration (90+ day) human-in-the-loop testing of advanced life support systems. Additionally, a 20' diameter vacuum chamber is being modified to create Mars atmospheric pressures and compositions. This chamber, designated the Mars Environment Chamber (MEC), will eventually be upgraded to include a dusty environment and thermal shroud to simulate conditions on the surface of Mars. In view that individual technologies will be in geographically diverse locations across NASA facilities and elsewhere in the world, schedule and funding constraints will likely limit the frequency of physical integration. When this is the case, absent subsystems can be either digitally or physically simulated. Using the Integrated Power Avionics and Software (iPAS) environment, HESTIA is able to bring together data from various subsystems in simulated surroundings, insert faults, errors, time delays, etc., and feed data into computer models or physical systems capable of reproducing the output of the absent subsystems for the consumption of a local subsystems. Although imperfect, this capability provides opportunities to test subsystem integration and interactions at a fraction of the cost. When a subsystem technology is too immature for integrated testing, models can be produced using the General-Use Nodal Network Solver (GUNNS) capability to simulate the overall system performance. In doing so, even technologies not yet on the drawing board can be integrated and overall system performance estimated. Through the integrated development of technologies, as well as of the infrastructure to rapidly and at a low cost, model, simulate, and test subsystem technologies early in their development, HESTIA is pioneering a new way of developing the future of human space exploration.

Banker, Brian F.↗

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

J Lemery↗

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

Medical Operations↗

Towards Sustainable Aviation With Efficient Airspace Operations

In November 2021, the Federal Aviation Administration published the United States Aviation Climate Action Plan to accelerate innovation across the U.S. aviation ecosystem. In response, NASA has established the Sustainable Flight National Partnership to engage with industry, academia, and other agencies to accomplish net-zero carbon emissions by 2050. As part of the SFNP Mission, NASA is conducting a series of real world operational demonstrations in the current National Airspace System with a focus on delivering real world sustainability benefits. This paper presents the current work and future plan for the SFNP Ops Demo Series and describes the cloud based infrastructure used for virtual deployment of decision support tools to flight operators and Air Traffic Controllers to help improve operational efficiency of the National Airspace System. Validation results are shared along with the key sustainability benefits such as jet fuel savings and reduction in CO2 emissions. The operational efficiency metrics such as delay savings are also reported.

Sustainable Flight National Partnership↗

Exploring Digital Transformation for NASA Nuclear Flight Safety

The U.S. National Aeronautics and Space Administration’s (NASA)’s Nuclear Flight Safety discipline is exploring opportunities to combine incremental advancements in many contributing areas in a way that produces a transformative change for how work is performed. More specifically, after providing some general NASA and space nuclear policy background, the authors will describe concepts and efforts that enable: (i) the use of objectives-d riven approaches (in concert with internal and external constraints) to establish a mission risk posture; (ii) the use of that risk posture in the planning process to risk-inform the selection of Safety and Mission Success (S&MS) methods and models; (iii) use of model-based and machine-assisted techniques to manage the complex and ponderous amount of information and interfaces that typify spaceflight efforts; (iv ) the means by which that infrastructure can directly feed an assurance case (including use of systems modelling language, ontological formulation, and semantic web technology) so as to address known weaknesses in our ability to communicate and manage that complexity; and (v) use of that case-assured framework to demonstrate that one did the adequate and sufficient S&MS work and that the S&MS work was done competently.

Donald Helton↗

Support of Helicopter 'Free Flight' Operations in the 1996 Olympics

The microcosm of activity surrounding the 1996 Olympic Games provided researchers an opportunity for demonstrating state-of-the art technology in the first large-scale deployment of a prototype digital communication/navigation/surveillance system in a confined environment. At the same time it provided an ideal opportunity for transportation officials to showcase the merits of an integrated transportation system in meeting the operational needs to transport time sensitive goods and provide public safety services under real-world conditions. Five aeronautical CNS functions using a digital datalink system were chosen for operational flight testing onboard 91 aircraft, most of them helicopters, participating in the Atlanta Short-Haul Transportation System. These included: GPS-based Automatic Dependent Surveillance, Cockpit Display of Traffic Information, Controller-Pilot Communications, Graphical Weather Information (uplink), and Automated Electronic Pilot Reporting (downlink). Atlanta provided the first opportunity to demonstrate, in an actual operating environment, key datalink functions which would enhance flight safety and situational awareness for the pilot and supplement conventional air traffic control. The knowledge gained from such a large-scale deployment will help system designers in development of a national infrastructure where aircraft would have the ability to navigate autonomously.

Branstetter, James R.↗

Low-Cost Telemetry System for Small/Micro Satellites

A Software Defined Radio (SDR) concept uses a minimum amount of analog/radio frequency components to up/downconvert the RF signal to/from a digital format. Once in the digital domain, all other processing (filtering, modulation, demodulation, etc.) is done in software. The project will leverage existing designs and enhance capabilities in the commercial sector to provide a path to a radiation-hardened SDR transponder. The SDR transponder would incorporate baseline technologies dealing with improved Forward Error Correcting (FEC) codes to be deployed to all Near Earth Network (NEN) ground stations. By incorporating this FEC, at least a tenfold increase in data throughput can be achieved. A family of transponder products can be implemented using common platform architecture, allowing new products to be more quickly introduced into the market. Software can be reused across products, reducing software/hardware costs dramatically. New features and capabilities, such as encoding and decoding algorithms, filters, and bit synchronizers, can be added to the existing infrastructure without requiring major new capital expenditures, allowing implementation of advanced features in the communication systems. As new telecommunication technologies emerge, incorporating them into the SDR fabric will be easily accomplished with little or no requirements for new hardware. There are no preferred flight platforms for the SDR technology, so it can be used on any type of orbital or sub-orbital platform, all within a fully radiation hardened design.

Sims, William↗

Enhanced Flight Termination System (EFTS): Flight Demonstration and Results

The Enhanced Flight Termination System (EFTS) program was initiated and propelled due to the inadvertent terminations of Global Hawk and the Strategic Target System and the NASA Inspector General's assessment letter and recommendations regarding the exploration of low-cost, lightweight space COMSEC for FTS. Additionally, the standard analog and high alphabet systems most commonly used in FTS are secure, but not encrypted. A study group was initiated to select and document a robust, affordable, reliable technology that provides encrypted FTS capability. A flight demonstration was conducted to gain experience using EFTS in an operational environment, provide confidence in the use of the EFTS components, integrate EFTS into an existing range infrastructure to demonstrate the scalability of system components, to provide a command controller that generated the EFTS waveform using an existing range infrastructure, and to provide a report documenting the results of the demonstration. The primary goal of the demonstration was to obtain operational experience with EFTS. Areas of operational experience include: mission planning, pre-flight configuration and testing, mission monitoring and recording, vehicle termination, developing mission procedures. and post mission data reduction and other post mission activities. An Advanced Medium-Range Air-to-Air Missile (AMRAAM) was selected to support the EFTS demonstration due to interest in future use of EFTS by the AMRAAM program, familiarity of EFTS by range personnel, and the availability of existing operational environment to support EFTS testing with available program funding. For demonstration purposes, the AMRAAM was successfully terminated using an EFTS receiver and successfully demonstrating EFTS. The EFTS monitoring software with spectrum analyzer and digital graphical display of aircraft, missile, and target were also demonstrated.

Tow, David↗

Factories-in-Space for Servicing, Assembly, & Manufacturing

Space 2.0 is a promising frontier for scientific exploration and the advancement of commerce, security, and technology. To effectively harness this potential, it is imperative to establish a multifunctional, resilient, and sustainable infrastructure that enables the maintenance and production of space-based systems. This capability is a driver for mission success on-orbit and for interplanetary travel to other celestial bodies. Central to this infrastructure is the establishment of orbital manufacturing facilities, referred to as 'factories-in-space' (FiS), which serve as critical nodes in the supply chain for the servicing, assembly, and production of systems essential for space-based operations. This paper presents a framework for understanding the key principles and design considerations underpinning FiS.

Technology↗