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

Abstract

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.
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Category

Academic article

Language

English

Author(s)

  • Dennis David Langer
  • Milica Orlandic
  • Sivert Bakken
  • Roger Birkeland
  • Joseph Landon Garrett
  • Tor Arne Johansen
  • Asgeir Johan Sørensen

Affiliation

  • SINTEF Ocean / Fisheries and New Biomarine Industry
  • Norwegian University of Science and Technology

Year

2023

Published in

Remote Sensing

Volume

15

Issue

15

View this publication at Norwegian Research Information Repository