Energy budgeting for CubeSats with an integrated FPGA

Abstract

CubeSats are a simple, low-cost option for developing quickly-deployable satellites, however, the tradeoff for these benefits is a small physical size, which restricts the CubeSat's solar panels' size and thus the available power budget and stored energy reserves. These power/energy limitations restrict the CubeSat's functionality and data processing capabilities, which makes leveraging CubeSats for compute-intensive missions challenging. Additionally, increasing sensor capabilities due to technological advances further compounds this functionality limitation, enabling sensors to gather significantly more data than a satellite's limited downlink bandwidth can accommodate. The influx in sensed data, which is particularly high for image-processing applications, introduces a pressing need for high-performance on-board data processing, which preprocesses and/or compresses the data before transmission. FPGAs have been incorporated into state-of-the-art satellites to provide high-performance on-board data processing, while simultaneously reducing the satellites' data processing energy consumption. However, even though FPGAs can provide these capabilities in full-scale satellites, a CubeSat's limited power budget makes integration of FPGAs into CubeSats a challenging task. For example, the commonly used Virtex4QV Radiation Tolerant FPGA family's average power consumption ranges from 1.25 to 12.5 Watts, whereas the CubeSat's power budget ranges from 2 to 8 Watts, with the smallest, cheapest CubeSat systems at the lower end of this range. Therefore, in order to successfully integrate FPGAs into CubeSats, the components' power consumptions must be clearly budgeted with respect to the CubeSat's specific functionalities and orbital pattern, which dictates the available power and stored energy reserves. In this paper, we present two detailed energy reserve budgeting case studies for FPGA-based CubeSats with respect to stored energy reserves for image compression and processing using a Canny edge detector. CubeSat designers can leverage this energy reserve budget with the application-specific components' power consumptions for applications such as hyper-spectral imaging (HSI), ground motion target indication (GMTI), and star tracking to quickly determine maximum payload operational time with respect to specific orbital patterns and mission requirements.