Comparison of Common Instrument Stack Architectures for Small UAS and CubeSats

Abstract

Both small satellites (e.g. CubeSats) and sUAS (small Unoccupied Aerial Systems) have a rapidly growing number of potential missions and can serve as platforms for a wide range of uses in science, communications, and remote sensing alone or together. The challenge is integrating these systems quickly and reliably with efficient payload operations. While much work has been completed to define and make flight control and operations available as open systems, fewer options exist for instrumentation. Some options are available for specific domains. For example, ROS (Robot Operating System) is used for many UAV (Unoccupied Aerial Vehicle) projects, but interdisciplinary use cases are non-trivial for projects that migrate payloads between UAVs and CubeSats or coordinate UAV and CubeSat joint missions. Common objectives and careful flight and ground configuration for both UAVs and CubeSats could provide a Common Instrument Stack Architecture (CISA). Many of the basic instrument integration objectives for CubeSats and sUAS share common requirements. The goal for the research architectures we are investigating, is to compare combinations of stack layers including: 1) the use of open source real-time operating systems (RTOS), such as FreeRTOS and Linux with real-time extensions, with 2) open middleware, such as ROS, cFS (core Flight System) or F Prime, and 3) image co-processing firmware. Previously developed and tested FPGA (Field Programmable Gate Array) and GP-GPU (General Purpose Graphics Processing Units) firmware for sUAS sensor networks will be integrated with CISA for performance testing. Ideally, we envision this architecture working for sensor networked flight instruments (sUAS and CubeSat) as well as ground systems (e.g. sUAS traffic management and CubeSat ground operations). To start, we are installing and evaluating the leading open-source middleware options in use for both UAVs and CubeSats integrated with our multi-core, GP-GPU, DPS, and FPGA image processing use cases to assess throughput, memory, I/O, storage, and power consumption. Our intent is to evaluate the relative merits of the underlying hardware architecture by running our prototype CISA (Common Instrument System Architecture) on off-the-shelf multi-core, GP-GPU, and FPGA SoCs (Systems-on-Chip) that have flown or are proposed for space flight, are in use with UAVs and provide best power efficiency and performance. This reference CISA stack composed of an SoC, operating system, co-processing, and middleware is hypothesized to allow future projects to migrate instrumentation and sensor payloads from UAVs to CubeSats easily and efficiently. Migration would provide continuity and scaling for research and science missions as well as joint operations. Along with objective metrics such as power and performance, the project is evaluating subjective metrics such as simplicity of integration, configuration, and interfacing common sensors.