Methods for Multisensory Detection of Light Phenomena on the Moon as a Payload Concept for a Nanosatellite Mission

• Main Author: Maurer, Andreas
• Format: Others
• Language: English
• Published: Luleå tekniska universitet, Rymdteknik 2020
• Subjects: Moon; TLP; Transient Lunar Phenomena; Image Processing; GPU; Nanosatellite; CubeSat; Nvidia Jetson Nano; OpenCL; CUDA; Telescope; Payload Concept; C/C++; background subtraction; connected component labelling; FPGA; Computer Systems; Datorsystem; Embedded Systems; Inbäddad systemteknik; Aerospace Engineering; Rymd- och flygteknik
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-80785

For 500 years transient light phenomena (TLP) have been observed on the lunar surface by ground-based observers. The actual physical reason for most of these events is today still unknown. Current plans of NASA and SpaceX to send astronauts back to the Moon and already successful deep-space CubeSat mission will allow in the future research nanosatellite missions to the cislunar space. This thesis presents a new hardware and software concept for a future payload on such a nanosatellite. The main task was to develop and implement a high-performance image processing algorithm which task is to detect short brightening flashes on the lunar surface. Based on a review of historic reported phenomena, possible explanation theories for these phenomena and currently active and planed ground- or space-based observatories possible reference scenarios were analyzed. From the presented scenarios one, the detection of brightening events was chosen and requirements for this scenario stated. Afterwards, possible detectors, processing computers and image processing algorithms were researched and compared regarding the specified requirements. This analysis of available algorithm was used to develop a new high-performance detection algorithm to detect transient brightening events on the Moon. The implementation of this algorithm running on the processor and the internal GPU of a MacMini achieved a framerate of 55 FPS by processing images with a resolution of 4.2 megapixel. Its functionality and performance was verified on the remote telescope operated by the Chair of Space Technology of the University of Würzburg. Furthermore, the developed algorithm was also successfully ported on the Nvidia Jetson Nano and its performance compared with a FPGA based image processing algorithm. The results were used to chose a FPGA as the main processing computer of the payload. This concept uses two backside illuminated CMOS image sensor connected to a single FPGA. On the FPGA the developed image processing algorithm should be implemented. Further work is required to realize the proposed concept in building the actual hardware and porting the developed algorithm onto this platform.