Implementing a Neural Network Execution Framework in Realistic Space Hardware and Software as a Pseudo On-Orbit Demonstration

Recent advances in hardware and software technology have made it possible to implement more resource-demanding deep learning algorithms in lighter hardware environments. This creates opportunities to use deep learning for space applications on increasingly lighter and smaller spacecraft. The goal of this work is to demonstrate the viability of implementing a Neural Network Execution Framework (NNEF) that can facilitate a cross-platform and unified deployment of any neural network onboard a spacecraft hardware and flight software. The NNEF generalizes the neural network inference process, regardless of the original framework in which they were created. This allows users to focus on the development of their scientific model architecture and deep learning objectives, rather than being distracted by the implementation process onboard the spacecraft. This framework has been implemented to run inside NASA\u27s core Flight System and on top of a Raspberry Pi 4 board, demonstrating the capability to execute a variety of trained neural networks created in Pytorch and Tensor Flow. This includes a neural-based compression algorithm used to process images from NASA\u27s Solar Dynamics Observatory in a space-like hardware-software configuration. This initial software implementation shows the feasibility of our goal, demonstrating the deployment of deep learning benefits through our framework in a unified way for a broader range of space missions and applications. In addition, for comparison purposes (not for benchmarking), it showed the performance of the networks running in the mentioned hardware-software configuration contrasted with the performance obtained in a regular computer environment

Simulation-To-Flight (STF-1): A Mission to Enable CubeSat Software-Based Validation and Verification

The Simulation-to-Flight 1 (STF-1) CubeSat mission aims to demonstrate how legacy simulation technologies may be adapted for flexible and effective use on missions using the CubeSat platform. These technologies, named NASA Operational Simulator (NOS), have demonstrated significant value on several missions such as James Webb Space Telescope, Global Precipitation Measurement, Juno, and Deep Space Climate Observatory in the areas of software development, mission operations/training, verification and validation (V&V), test procedure development and software systems check-out. STF-1 will demonstrate a highly portable simulation and test platform that allows seamless transition of mission development artifacts to flight products. This environment will decrease development time of future CubeSat missions by lessening the dependency on hardware resources. In addition, through a partnership between NASA GSFC, the West Virginia Space Grant Consortium and West Virginia University, the STF-1 CubeSat will hosts payloads for three secondary objectives that aim to advance engineering and physical-science research in the areas of navigation systems of small satellites, provide useful data for understanding magnetosphere-ionosphere coupling and space weather, and verify the performance and durability of III-V Nitride-based materials

NASA Operational Simulator for SmallSats (NOS3) – Design Reference Mission

The NASA Operational Simulator for Small Satellites (NOS3) has undergone significant advances including updating the framework to be component based and expanding the open-source code to include a generic design reference mission to enable advanced technologies. This paper details the changes to the framework as well as a number of innovative use-cases the team is currently supporting such as 1) the expansion of NOS3 to support distributed systems missions in collaboration with NASA GSFC, 2) the integration of NASA JPL’s Science Yield improvemeNt via Onboard Prioritization and Summary of Information Systems (SYNOPSIS) for on-orbit science data prioritization, and 3) the inclusion of NASA IV&V JSTAR’s software-only CCSDS encryption library (CryptoLib). NOS3 continues to serve the SmallSat community by providing an open-source digital twin that can significantly reduce costs associated with spacecraft software development, test, and operations. The NOS3 team plans to continue to expand the resources available to the community and partner with others to resolve issues and add new features requested via the NASA GitHub