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At least 145 records · Page 8

NASP - Enabling new space launch options

Successful NASP developments in the United States are bringing about the possibility of effective, fully reusable vehicles for transport of people and cargo between earth and space. These developments include: extension of airbreathing propulsion to a much higher speed; densification of propellants for greater energy per unit volume of mass; structures with much greater strength-to-weight at high temperatures; computational advancements that enable more optimal design and integration of airframes, engines and controls; and advances in avionics, robotics, artificial intelligence and automation that enable accomplishment of earth-to-orbit (ETO) operations with much less manpower support and cost. This paper describes the relative magnitude of improvement that these developments may provide.

Froning, David↗

A graphical workstation based part-task flight simulator for preliminary rapid evaluation of advanced displays

Advances in avionics and display technology are significantly changing the cockpit environment in current transport aircraft. The MIT Aeronautical Systems Lab (ASL) developed a part-task flight simulator specifically to study the effects of these new technologies on flight crew situational awareness and performance. The simulator is based on a commercially-available graphics workstation, and can be rapidly reconfigured to meet the varying demands of experimental studies. The simulator was successfully used to evaluate graphical microbursts alerting displays, electronic instrument approach plates, terrain awareness and alerting displays, and ATC routing amendment delivery through digital datalinks.

Wanke, Craig↗

A graphical workstation based part-task flight simulator for preliminary rapid evaluation of advanced displays

Advances in avionics and display technology are significantly changing the cockpit environment in current transport aircraft. The MIT Aeronautical Systems Lab (ASL) has developed a part-task flight simulator specifically to study the effects of these new technologies on flight crew situational awareness and performance. The simulator is based on a commercially-available graphics workstation, and can be rapidly reconfigured to meet the varying demands of experimental studies. The simulator has been successfully used to evaluate graphical microburst alerting displays, electronic instrument approach plates, terrain awareness and alerting displays, and ATC routing amendment delivery through digital datalinks.

Wanke, Craig↗

MIDEX Advanced Modular and Distributed Spacecraft Avionics Architecture

MIDEX (Medium Class Explorer) is the newest line in NASA's Explorer spacecraft development program. As part of the MIDEX charter, the MIDEX spacecraft development team has developed a new modular, distributed, and scaleable spacecraft architecture that pioneers new spaceflight technologies and implementation approaches, all designed to reduce overall spacecraft cost while increasing overall functional capability. This resultant "plug and play" system dramatically decreases the complexity and duration of spacecraft integration and test, providing a basic framework that supports spacecraft modularity and scalability for missions of varying size and complexity. Together, these subsystems form a modular, flexible avionics suite that can be modified and expanded to support low-end and very high-end mission requirements with a minimum of redesign, as well as allowing a smooth, continuous infusion of new technologies as they are developed without redesigning the system. This overall approach has the net benefit of allowing a greater portion of the overall mission budget to be allocated to mission science instead of a spacecraft bus. The MIDEX scaleable architecture is currently being manufactured and tested for use on the Microwave Anisotropy Probe (MAP), an inhouse program at GSFC.

Ruffa, John A.↗

The Deep Space 4/Champollion Comet Rendezvous and Lander Technology Demonstration Mission

The Deep Space 4/Champollion mission is designed to test and validate technologies for landing on and anchoring to small bodies, and sample collection and transfer, in preparation for future sample return missions from comets, asteroids, and satellites. in addition, DS-4 will test technologies for advanced, multi-engine solar electric propulsion (SEP) systems, inflatable-rigidizable solar arrays, autonomous navigation and precision guidance for landing, autonomous hazard detection and avoidance, and advanced integrated avionics and packaging concepts. Deep Space-4/Champollion consists of two spacecraft: an orbiter/carrier vehicle which includes the multi-engine SEP stage, and a lander, called Champollion, which will descend to the surface of the 46P/Tempel 1 cometary nucleus. The spacecraft will launch in April, 2003 and land on the comet in September, 2006 Deep Space 4/Champollion is a joint project between NASA and CNES, the French space agency.

Smythe, William D.↗

Advanced Launch Technology Life Cycle Analysis Using the Architectural Comparison Tool (ACT)

Life cycle technology impact comparisons for nanolauncher technology concepts were performed using an Affordability Comparison Tool (ACT) prototype. Examined are cost drivers and whether technology investments can dramatically affect the life cycle characteristics. Primary among the selected applications was the prospect of improving nanolauncher systems. As a result, findings and conclusions are documented for ways of creating more productive and affordable nanolauncher systems; e.g., an Express Lane-Flex Lane concept is forwarded, and the beneficial effect of incorporating advanced integrated avionics is explored. Also, a Functional Systems Breakdown Structure (F-SBS) was developed to derive consistent definitions of the flight and ground systems for both system performance and life cycle analysis. Further, a comprehensive catalog of ground segment functions was created.

Space Flight Architecture↗

NASA SpaceCube Intelligent Multi-Purpose System for Enabling Remote Sensing, Communication, and Navigation in Mission Architectures

New, innovative CubeSat mission concepts demand modern capabilities such as artificial intelligence and autonomy, constellation coordination, fault mitigation, and robotic servicing –all of which require vastly more processing resources than legacy systems are capable of providing. Enabling these domains within a scalable, configurable processing architecture is advantageous because it also allows for the flexibility to address varying mission roles, such as a command and data-handling system, a high-performance application processor extension, a guidance and navigation solution, or an instrument/sensor interface. This paper describes the NASA SpaceCube Intelligent Multi-Purpose System (IMPS), which allows mission developers to mix-and-match 1U (10 cm × 10 cm) CubeSat payloads configured for mission-specific needs. The central enabling component of the system architecture to address these concerns is the SpaceCube v3.0 Mini Processor. This single-board computer features the 20nm Xilinx Kintex UltraScale FPGA combined with a radiation-hardened FPGA monitor, and extensive IO to integrate and interconnect varying cards within the system. To unify the re-usable designs within this architecture, the CubeSat Card Standard was developed to guide design of 1U cards. This standard define spinout configurations, mechanical, and electrical specifications for 1U CubeSat cards, allowing the backplane and mechanical enclosure to be easily extended. NASA has developed several cards adhering to the standard (System-on-Chip, power card, etc.), which allows the flexibility to configure a payload from a common catalog of cards.

Advanced Avionics, Hybrid Processing, Data Process↗

A Novel RF Architecture for Simultaneous Communication, Navigation, and Remote Sensing with Software-Defined Radio

The rapid growth of SmallSat and CubeSat missions at NASA has necessitated a re-evaluation of communication and remote-sensing architectures. Novel designs for CubeSat-sized single-board computers can now include larger Field-Programmable Gate Arrays (FPGAs) and faster System-on-Chip (SoCs) devices. These components substantially improve onboard processing capabilities so that varying subsystems no longer require an independent processor. By replacing individual Radio Frequency (RF) systems with a single software-defined radio (SDR) and processor, mission designers have greater control over reliability, performance, and efficiency. The presented architecture combines individual processing systems into a single design and establishes a modular SDR architecture capable of both remote-sensing and communication applications. This new approach based on a multi-input multi-output (MIMO) SDR features a scalable architecture optimized for Size, Weight, Power, and Cost (SWaP-C), with sufficient noise performance and phase-coherence to enable both remote-sensing and navigation applications, while providing a communication solution for simultaneous S-band and X-band transmission. This SDR design is developed around the NASA CubeSat Card Standard (CS2) that provides the required modularity through simplified backplane and interchangeable options for multiple radiation-hardened/tolerant processors. This architecture provides missions with a single platform for high-rate communication and a future platform to develop cognitive radio systems.

Advanced Avionics, Hybrid Processing, Data Process↗

Signal and Power Integrity Design Methodology for High-Performance Flight Computing Systems

Computing capabilities of space systems have in-creased onboard performance by orders of magnitude with the use of radiation-tolerant field-programmable gate arrays (FPGA)and processors. The incorporation of signal and power integrity analysis with printed circuit board (PCB) design in reliable computing architectures for space systems has become critical to enable future mission capabilities. Developers launch high-performance processors into a breadth of orbits and missions, running varying applications that create challenges for designing reliable computing hardware. Specifically, for these designs, academic and industry research has focused on component radiation performance, fault mitigation, and reliable architectures. How-ever, other design parameters including electromagnetic interference (EMI), PCB stackup, signal integrity (SI), voltage regulator module (VRM) design, and power distribution network (PDN)are often deprioritized or disregarded as the design matures. Since these characteristics are becoming more significant in high-performance processor designs, this research presents a hardware design and analysis methodology for high-performance, space-computing systems that focuses on a holistic design approach and PDN reliability. While these challenges exist across all space hardware, the reduced PCB dimensions imposed by SmallSats and CubeSats introduce additional hurdles, specifically to VRM and decoupling design. By examining the relationship between the PDN and radiation performance, an analytical relationship is developed that incorporates Total Ionizing Dose and Single-Event Transients to ensure reliability throughout the mission duration. The presented design methodology is applied to the SpaceCube v3.0 Mini, an FPGA-based on-board science data processing system developed at NASA Goddard Space Flight Center.

Advanced avionics↗

NASA SpaceCube Edge TPU SmallSat Card for Autonomous Operations and Onboard Science-Data Analysis

Using state-of-the-art artificial intelligence (AI)frameworks onboard spacecraft is challenging because common spacecraft processors cannot provide comparable performance to datacenters with server-grade CPUs and GPUs available for terrestrial applications and advanced deep-learning networks. This limitation makes small, lo w-p o we r AI microchip architectures, such as the Google Coral Edge Tensor Processing Unit (TPU), attractive for space missions where the application-specific design enables both high-performance and power-efficient computing for AI applications. To address these challenging considerations for space deployment, this research introduces the design and capabilities of a CubeSat-sized Edge TPU-based co-processor card, known as the SpaceCube Low-power Ed g e Artificial Intelligence Resilient Node (SC-LEARN). This design conforms to NASA’s CubeSat Card Specification (CS2) for integration into next-generation SmallSat and CubeSat systems. This paper describes the overarching architecture and design of the SC-LEARN, as well as, the supporting test card designed for rapid prototyping and evaluation. The SC-LEARN was developed with three operational modes: (1) a high-performance parallel-processing mode,(2)a fault-tolerant mode for onboard resilience, and (3) a power-saving mode with cold spares. Importantly, this research also elaborates on both training and quantization of Tensor Flow models for the SC-LEARN for use onboard with representative, open-source datasets. Lastly, we describe future research plans, including radiation-beam testing and flight demonstration.

Advanced avionics↗

Onboard Hyperspectral Image Classification via Transfer Learning for Communication-Limited Spacecraft

Employing deep-learning and artificial-intelligence (AI) techniques onboard spacecraft can dramatically improve priority data selection to ensure more effective use of the available downlink. However, deployment of effective deep-learning models requires significant training on the ground, which may not be feasible, due to limited data available in an unexplored environment. Therefore, this research explores building robust classification models for onboard data processing where training data is highly limited using transfer-learning techniques. In this paper, we focus on the use case of hyperspectral imaging for remote sensing, a domain where the high dimensionality of the data from the sensor can rapidly saturate the downlink bandwidth. With this bottleneck, there is an impending need to autonomously and robustly classify data onboard to optimize downlink of high-impact measurements, thus maximizing the scientific utility per bit transmitted to the ground. This paper examines the use of deep neural networks onboard for hyperspectral image classification in a communication-limited scenario to analyze how the models perform with limited training data. The use of transfer learning can ameliorate the issue of poor generalization by transferring features learned from training on a large source dataset for one classification task to the target classification task with limited training data. For two deep-learning models from literature, we compare the accuracy of the models trained using transfer learning to models trained from scratch using a random weight initialization with varying amounts of training data. We demonstrate the feasibility and performance of running inference of the deep-learning models on representative flight-like hardware.

Advanced Avionics, Machine Learning, Data Processi↗

Advanced Launch System Multi-Path Redundant Avionics Architecture Analysis and Characterization

The objective of the Multi-Path Redundant Avionics Suite (MPRAS) program is the development of a set of avionic architectural modules which will be applicable to the family of launch vehicles required to support the Advanced Launch System (ALS). To enable ALS cost/performance requirements to be met, the MPRAS must support autonomy, maintenance, and testability capabilities which exceed those present in conventional launch vehicles. The multi-path redundant or fault tolerance characteristics of the MPRAS are necessary to offset a reduction in avionics reliability due to the increased complexity needed to support these new cost reduction and performance capabilities and to meet avionics reliability requirements which will provide cost-effective reductions in overall ALS recurring costs. A complex, real-time distributed computing system is needed to meet the ALS avionics system requirements. General Dynamics, Boeing Aerospace, and C.S. Draper Laboratory have proposed system architectures as candidates for the ALS MPRAS. The purpose of this document is to report the results of independent performance and reliability characterization and assessment analyses of each proposed candidate architecture and qualitative assessments of testability, maintainability, and fault tolerance mechanisms. These independent analyses were conducted as part of the MPRAS Part 2 program and were carried under NASA Langley Research Contract NAS1-17964, Task Assignment 28.

Baker, Robert L.↗

Advanced Spacesuit Informatics Software Design for Power, Avionics and Software Version 2.0

A description of the software design for the 2016 edition of the Informatics computer assembly of the NASAs Advanced Extravehicular Mobility Unit (AEMU), also called the Advanced Spacesuit. The Informatics system is an optional part of the spacesuit assembly. It adds a graphical interface for displaying suit status, timelines, procedures, and warning information. It also provides an interface to the suit mounted camera for recording still images, video, and audio field notes.

Instrumentation↗