Implementation of the Φsat-2 on board image processing chain

N. Melega; Bernardo A. Carnicero; N. Longepe; A. Paskeviciute; V. Marchese; Oriol Aragon; Irina Babkina; Alessandro Marin; Jakub Nalepa; Leonie Buckley; Giorgia Guerrisi; Sofia Oliviera; Hano Stein

doi:10.1117/12.2679044

19 October 2023 Implementation of the Φsat-2 on board image processing chain

N. Melega, Bernardo A. Carnicero, N. Longepe, A. Paskeviciute, V. Marchese, Oriol Aragon, Irina Babkina, Alessandro Marin, Jakub Nalepa, Leonie Buckley, Giorgia Guerrisi, Sofia Oliviera, Hano Stein

Author Affiliations +

Proceedings Volume 12729, Sensors, Systems, and Next-Generation Satellites XXVII; 127290Z (2023) https://doi.org/10.1117/12.2679044
Event: SPIE Remote Sensing, 2023, Amsterdam, Netherlands

Abstract

The Φsat-2 mission from the European Space Agency (ESA) is part of Φsat mission lineup aimed to address innovative mission concepts making use of advanced onboard processing including Artificial Intelligence. Φsat-2 is based on a 6U CubeSat with a medium-high resolution VIS/NIR multispectral payload (eight bands plus NIR) combined with a hardware accelerated unit capable of running several AI applications throughout the mission lifetime. As images are acquired, and after the application of dTDI processing, the raw data is transferred through SpaceWire to a payload pre-processor where level L1B will be produced. At this stage radiometric and geometric processing are carried out in conjunction with georeferencing. Once the data is pre-processed, it is fed to the AI processor through the primary computer and made available to the onboard applications; orchestration is done via a dedicated version of the NanoSat MO Framework. The following applications are currently baselined and additional two will be selected via dedicated AI Challenge by Q3 2023: SAT2MAP for autonomous detection of streets during emergency scenarios; Cloud Detection application and service for data reduction; the Autonomous Vessel Awareness to detect and classify vessel types and the deep compression application (CAE) that has the goal of reducing the amount of acquired data to improve the mission effectiveness.

Conference Presentation

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

N. Melega, Bernardo A. Carnicero, N. Longepe, A. Paskeviciute, V. Marchese, Oriol Aragon, Irina Babkina, Alessandro Marin, Jakub Nalepa, Leonie Buckley, Giorgia Guerrisi, Sofia Oliviera, and Hano Stein "Implementation of the Φsat-2 on board image processing chain", Proc. SPIE 12729, Sensors, Systems, and Next-Generation Satellites XXVII, 127290Z (19 October 2023); https://doi.org/10.1117/12.2679044

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