Science [&] Technology Norway (NO)
The amount of data coming from imaging sensors increases steadily and a modern imaging sensor creates frames of several megapixels at a high frame acquisition rate. These imaging sensors with their large data output are mounted on spaceborne platforms, but the downlink capability of these spaceborne platforms, especially for small platforms, has not been increasing at the same rate as the data generation of the imaging sensors. This has resulted in a ‘big data problem’ on board these spaceborne platforms. An industry trend towards smaller satellites – with smaller antennas, less power and worse pointing accuracy- leads to an expectation that the downlink capability will remain well below the data generation capability for such imaging satellites. In order to use more acquisitions and have a high ‘usability’ of the satellite, the on-board processing of payload data is a solution.
In this project, S&T will determine and test the technology platform that is best suited for onboard intelligent processing of imaging payload data. This will include testing techniques such as development of low volume data products instead of raw image files for downlink, verifying using concrete algorithms and implementation choices how performant such processing can be, exploring the implications of moving certain parts of the processing functionality to FPGA and conducting tests using HyperSpectral imagery on a cubesat.