Robust and Reconfigurable On-Board Processing for a Hyperspectral Imaging Small Satellite

Hyperspectral imaging is a powerful remote sensing technology, but its use in space is limited by the large volume of data it produces, which leads to a downlink bottleneck. Therefore, most payloads to date have been oriented towards demonstrating the scientific usefulness of hyperspectral data sporadically over diverse areas rather than detailed monitoring of spatio-spectral dynamics. The key to overcoming the data bandwidth limitation is to process the data on-board the satellite prior to downlink. In this article, the design, implementation, and in-flight demonstration of the on-board processing pipeline of the HYPSO-1 cube-satellite are presented. The pipeline provides not only flexible image processing but also reliability and resilience, characterized by robust booting and updating procedures. The processing time and compression rate of the simplest pipeline, which includes capturing, binning, and compressing the image, are analyzed in detail. Based on these analyses, the implications of the pipeline performance on HYPSO-1's mission are discussed.

Automated summary

Hyperspectral imaging is a valuable technology for remote sensing, but its application in space is limited by the large amount of data it generates and the subsequent bottleneck in data transmission. To overcome this limitation, an on-board processing pipeline for the HYPSO-1 cube-satellite is developed, providing flexible image processing, reliability, and resilience. The performance of the pipeline, including processing time and compression rate, is analyzed, and the implications for the HYPSO-1 mission are discussed.