Payload verification and testing for the CSIROSat-1 mission
Abstract
CSIRO (Commonwealth Scientific and Industrial Research Organisation (Australia)) has been working on the design aspects of its first CubeSat mission, known as CSIROSat-1, together with Inovor Technologies (an Australian space start-up company). The satellite is primarily intended to extend Australian Earth Observation capability. CSIROSat-1 will be uplifted to the ISS and then launched into a LEO orbit in late 2021 or early 2022. The recent outbreak of bushfires across Australia highlights the influence of climate change on our ecosystems. Among the key capabilities of the imager in this satellite will be the ability to accurately monitor the water content in forest canopies. We plan to use spectral reflectance of trees in areas of variable rainfall and groundwater to monitor the seasonal variation of the forest canopies in arid regions that are currently under study by CSIRO Land & Water. While evapotranspiration can be estimated using MODIS data that is validated using field measurement of evapotranspiration, the large pixel size (250m) and small number of SWIR bands limit the power of this method. CSIROSat-1 will provide 120m pixels and many more SWIR spectral bands than are currently publicly available at that resolution. The payload for our 3U CubeSat includes a hyperspectral payload imager, a SWIR camera, lens and a filter, together with an on-board processor. An ambitious in-orbit, re-programmable high performance on-board processor will form part of our mission and will be coupled with post-processing imaging capabilities on the ground to account for jitter and variability in pitch, yaw and roll motions to learn from the key parameters that require tweaking to maximise the quality of the data products. The optimised parameters will then be incorporated into a new FPGA image that will be uploaded to CSIROSat-1 as the mission progresses. Results of the early testing and verification of functionality will be presented highlighting challenges and status of testing to-date. Lessons learned from the integration of our CubeSat into the ISS will also be presented.
- Publication:
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43rd COSPAR Scientific Assembly. Held 28 January - 4 February
- Pub Date:
- January 2021
- Bibcode:
- 2021cosp...43E..49R