Towards a Radiation-Tolerant Display System
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Engineering topics
Publications and source records attributed to Alan George.
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Distributed space systems are a mission architecture consisting of multiple spacecraft as a cohesive system which provide multipoint sampling, increased mission coverage, or improved sample resolution, while reducing mission risk through redundancy. To fully realize the potential of these systems, eventually scaling to hundreds or thousands of spacecraft, distributed space systems need to be operated as a single entity, which will enable a variety of novel scientific space missions. The Distributed Spacecraft Autonomy (DSA) project is a software project which aims to mature the technology needed for those systems, namely autonomous decision-making and swarm networking. The DSA project leverages a containerized swarm test framework to simulate spacecraft software, which can identify emergent behavior early in development. Container virtualization allows distributed spacecraft systems to be simulated entirely in software on a single computer, avoiding the overhead associated with conventional approaches like hardware facsimiles and virtual machines. For this approach to be effective, the simulated system behavior must not be artificially influenced by the swarm test framework itself. To address this, we present a series of benchmarks to quantify virtual network bandwidth available on a single-host computer and contextualize this against the network and application behavior of the DSA swarm test framework.
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.
As space mission design trends towards shared, multi-mission platforms and high-performance onboard computing architectures, the number of spacecraft launched into operation is also steadily rising. Through ridesharing, spacecraft miniaturization, and other cost-reduction measures, the barriers to space are lowering, resulting in compounded growth in the amount of flight software being deployed. To meet the needs of both the growing quantity and evolving nature of spacecraft, flight software design must accordingly adapt to support more efficient development, solutions to computational resource-sharing, and software reusability. This paper focuses on a software payload demonstrating several core technologies that improve the state-of-the-art in these identified areas. Launched into low-earth orbit in January 2022, our software payload was conceived, designed, and delivered in a span of merely two months. It was developed on top of the NASA core Flight System (cFS) framework and the Distributed Spacecraft Autonomy (DSA) Comm cFS application, which translates cFS software bus messages across a Data Distribution Service (DDS) network. The flight software, packaged in Linux container images, was deployed as one of 18 flight applications managed through the Unibap SpaceCloud Framework. The applications were run on a Unibap iX5-102 radiation-tolerant payload computer, hosted on the D-Orbit SCV-004 spacecraft as part of an ESA-sponsored in-orbit technology test. Our payload, referred to as the DSA D-Orbit software, demonstrates the reusability of the DSA Comm app in a substantially different context and purpose as its original mission. Comm’s original design goal was to reliably distribute messages between spacecraft swarms of arbitrary size and dynamic network topology. However, we leverage this same functionality to introduce redundancy and opportunistic parallel data processing in the context of a representative onboard image processing workload. This adaptive mission architecture was enabled in part by the SpaceCloud Framework’s use of container virtualization as the payload integration interface. By using a base container image with common high-level language runtimes and libraries, we were able to rapidly design, develop, and validate our image processing application without many of the technological barriers common to flight software development. We present details the goals, approach, results, and lessons learned through this technology demonstration experiment and contextualize those observations against present and future challenges in spacecraft software development.