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6 August 2015Research on optimal path planning algorithm of task-oriented optical remote sensing satellites
GEO task-oriented optical remote sensing satellite, is very suitable for long-term continuous monitoring and quick access
to imaging. With the development of high resolution optical payload technology and satellite attitude control technology,
GEO optical remote sensing satellites will become an important developing trend for aerospace remote sensing satellite
in the near future. In the paper, we focused on GEO optical remote sensing satellite plane array stare imaging
characteristics and real-time leading mission of earth observation mode, targeted on satisfying needs of the user with the
minimum cost of maneuver, and put forward the optimal path planning algorithm centered on transformation from
geographic coordinate space to Field of plane, and finally reduced the burden of the control system. In this algorithm,
bounded irregular closed area on the ground would be transformed based on coordinate transformation relations in to the
reference plane for field of the satellite payload, and then using the branch and bound method to search for feasible
solutions, cutting off the non-feasible solution in the solution space based on pruning strategy; and finally trimming some
suboptimal feasible solutions based on the optimization index until a feasible solution for the global optimum.
Simulation and visualization presentation software testing results verified the feasibility and effectiveness of the strategy.
Yunhe Liu,Shengli Xu,Fengjing Liu, andJingpeng Yuan
"Research on optimal path planning algorithm of task-oriented optical remote sensing satellites", Proc. SPIE 9669, Remote Sensing of the Environment: 19th National Symposium on Remote Sensing of China, 96690I (6 August 2015); https://doi.org/10.1117/12.2204736
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Yunhe Liu, Shengli Xu, Fengjing Liu, Jingpeng Yuan, "Research on optimal path planning algorithm of task-oriented optical remote sensing satellites," Proc. SPIE 9669, Remote Sensing of the Environment: 19th National Symposium on Remote Sensing of China, 96690I (6 August 2015); https://doi.org/10.1117/12.2204736