Energy budgeting for CubeSats with an integrated FPGA

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 p- ocessing 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.