A Vision Based Sensor System For Spacecraft Relative Navigation
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Docking is one of the crucial key elements in many aerospace applications and missions where despite all endeavors and precautions accidents and incidents occur far too often. Those events can lead in the worst case scenario to a total loss of the space system and payload. To better understand, manage and control those situations and to test and simulate the docking process between two spacecrafts, the space maneuvering and docking facility has been built and developed by the chair of aerospace information technology at the university of Würzburg. The facility consists out of several floating vehicles which should be able to execute an autonomously docking maneuver.
In this master thesis, a vision based sensor system for the space maneuvering and docking facility was designed, developed and implemented. The system is mounted on top of the approaching vehicle to perform a close range proximity maneuver through computer vision relative navigation. The required hardware and software components were investigated and a suitable system was built. To achieve the required level of accuracy for relative navigation, the sensor data from the vision based system and the proximity sensor is filtered, fused and subsequently delivered to the navigation, guidance and control unit of the host spacecraft and to the ground station. Network traffic between the entities is transmitted over an implemented network protocol which is based on the fourth layer of the OSI model to guarantee a reliable data transfer. The emphasis of this thesis is based on the research and evaluation of suitable object detection algorithms and the implementation of them under the required real time constraints. Furthermore, the position and orientation of the target spacecraft is determined by a newly developed approach that is merging computer vision methods with high level intelligence processing, data fusion and GPU-accelerated computing on a powerful embedded processing platform.
Place, publisher, year, edition, pages
2016. , 83 p.
Engineering and Technology
IdentifiersURN: urn:nbn:se:ltu:diva-60551OAI: oai:DiVA.org:ltu-60551DiVA: diva2:1047915
Space Engineering, master's level
Redah, Atheel, M.Sc. Eng.
Montenegro, Sergio, Prof. Dr.Enmark, Anita, Dr.