Fast and energy saving onboard sensor data processing software for CubeSats

Overview of onboard software for CubeSat

The growing demand of space-related applications, has made research CubeSat onboard software enticing because of their numerous applications and low design-and-deployment cost. The new paradigm of connected space through CubeSats makes possible a wide range of applications, such as Earth remote sensing, space exploration, and rural connectivity. CubeSats further provide a complementary connectivity solution to the pervasive Internet of Things (IoT) networks, leading to a globally connected cyber-physical system.

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.

Onboard Data processing for CubeSats

Several data processing solutions have been studied for CubeSat on-board data processing:

  1. The use of FPGAs, i.e., programable hardware, can reduce power consumption and increase data processing, however high complexity in programming is the main drawback of FPGA.
  2. GPUs are probably the fastest data processing processors today. However, large power consumption, thermal load and performance bottlenecks in data transfer to GPU memory reduce their appeal in-space applications.

Klepsydra SDK: more onboard data processing with less power

Figure 1 shows comparison of these data processing solutions. These solutions, without a high performance data processing accompanying them, are unable to meet power budget and/or data processing requirements.

Klepsydra has developed an advanced software framework for onboard computing applications providing best-in-class data processing performance whilst significantly reducing latency and power consumption. This software can be used standalone or combined with FPGA. In either case, Klepsydra outperforms standard data processing solutions for CubeSats.

Figure 1. Comparative of data processing approaches

Performance and power consumption benchmark

Klepsydra has run performance benchmarks for large volumes of data processing in different scenarios for space data applications.

The following two figures show performance vs power consumption benchmarks for Xilinx ZedBoard and for a Space-certified microcontroller respectively.

Xilinx data throughput

These benchmarks compare Klepsydra software against a traditional data processing technique.

They show that Klepsydra gives users the freedom to decide to:

  • Process substantially more data using the same power (CPU)
  • Process the same amount of data and dramatically reduce power consumption.
  • Or a combination of both of these.

Figure 3

GR716 data throughput


Utilisation in CubeSats for Remote Sensing

Remote sensing on-board data processing can fully take advantage of Klepsydra software, which translates into the following benefits:

  • Increase processing on-board to compress data and hence reduce downlink time.
  • Implement intelligent data analysis solution (e.g.AI-based image selection) on-board reducing data volumen for downlink.

Utilisation for Telecom and Constellations

Increasing on-board data processing achieved with Klepsydra can bring benefits like:

  • Increase revenues for telecom companies, as more paid requests from customers can be processed and with lower latency
  • Improve CubeSat constellation position with a tighter network and distributed computing applications.

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