面向区域成像任务的环月卫星侧摆角优化方法
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摘要
面向月表大区域成像任务需求,提出了拼接成像侧摆角优化方法。针对区域覆盖率计算,提出了基于矢量多边形逻辑运算的成像覆盖率快速计算方法,可在保证计算精度的同时降低计算复杂度;构建拼接成像任务侧摆角优化模型,采用基于sigmoid函数的自适应遗传算法求解;并采用两组仿真数据验证了该优化算法的可行性。
The lunar surface topography mapping is the basic work of the lunar exploration and plays an important role in the three-phase("around-fall-back") lunar exploration program. In the "around" phase, it is necessary to use the camera carried by the spacecraft to acquire high-resolution image of area around the drop-off point. Due to the low orbit altitude and the limited field of view of camera, the width of the imagery obtained by the lunar satellite is relatively small compared to the range of the required drop-off area. Multiple strips stitching is an effective and practical way to solve large regional imaging problem. In a given multiple strips stitching task planning, it is required to optimize the side-swing angle of each orbit within a given mission duration to meet the regional coverage demand. To meet the requirements of region multiple strip stitched imaging task,an lateral swing optimization of method is proposed in this paper. Firstly, a fast algorithm based on vector polygon logical operation is proposed. Coverage polygons of each imaging strip are calculated based on the lateral swing angle, satellite orbit and the field of view of the sensor, then the coverage ratio can be computed via a Boolean operation between target polygon and strip coverage polygons. The proposed method of coverage ratio calculation can not only ensure the accuracy of calculation, but also can dramatically reduce its computation complexity. Secondly, a lateral swing angle optimization model for multiple strip stitching imaging task is introduced, which uses swing angle as decision valuables, coverage ration maximization as objective function respectively, and an improved adaptive genetic algorithm based on sigmoid function is proposed to solve the optimization model. Finally, two simulation experiments are executed to validate the validity of proposed method.
The lunar surface topography mapping is the basic work of the lunar exploration and plays an important role in the three-phase("around-fall-back") lunar exploration program. In the "around" phase, it is necessary to use the camera carried by the spacecraft to acquire high-resolution image of area around the drop-off point. Due to the low orbit altitude and the limited field of view of camera, the width of the imagery obtained by the lunar satellite is relatively small compared to the range of the required drop-off area. Multiple strips stitching is an effective and practical way to solve large regional imaging problem. In a given multiple strips stitching task planning, it is required to optimize the side-swing angle of each orbit within a given mission duration to meet the regional coverage demand. To meet the requirements of region multiple strip stitched imaging task,an lateral swing optimization of method is proposed in this paper. Firstly, a fast algorithm based on vector polygon logical operation is proposed. Coverage polygons of each imaging strip are calculated based on the lateral swing angle, satellite orbit and the field of view of the sensor, then the coverage ratio can be computed via a Boolean operation between target polygon and strip coverage polygons. The proposed method of coverage ratio calculation can not only ensure the accuracy of calculation, but also can dramatically reduce its computation complexity. Secondly, a lateral swing angle optimization model for multiple strip stitching imaging task is introduced, which uses swing angle as decision valuables, coverage ration maximization as objective function respectively, and an improved adaptive genetic algorithm based on sigmoid function is proposed to solve the optimization model. Finally, two simulation experiments are executed to validate the validity of proposed method.
引文
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[12]Ren Ziwu,San Ye.Improved Adaptive Genetic Algorithm and Its Application Research in Parameter Identification[J].Journal of System Simulation,2006,18(1):41-43(任子武,伞冶.自适应遗传算法的改进及在系统辨识中应用研究[J].系统仿真学报,2006,18(1):41-43)
[13]Shi Shan,Li Qingfu,Wang Xinghua.Optimum Design of Brushless DC Motor Based on Adaptive Genetic Algorithm[J].Journal of Xi’an Jiaotong University,2002,36(12):1 215-1 218(石山,励庆孚,王兴华.基于自适应遗传算法的无刷直流电机的优化设计[J].西安交通大学学报,2002,36(12):1 215-1 218)
[14] Mazarico E,Rowlands D,Neumann G A,et al.Orbit Determination of the Lunar Reconnaissance Orbiter[J].Journal of Geodesy,2012,86(3):193-207
[15]Zheng Yongchun,Zou Yongliao,Fu Xiaohui.LRO and LCROSS Missions:Overview and Enlightenment for Future Lunar Exploration[J].Spacecraft Engineering,2011,20(4):117-129(郑永春,邹永廖,付晓辉.LRO和LCROSS探月计划:科学探测的分析与启示[J].航天器工程,2011,20(4):117-129)
[2] Zhu Jianghan,Li Xi,Mao Chilong,et al.Elevations Selection Approach of Area Target Observation Task Using Satellites Resource[J].Geomatics and Information Science of Wuhan University,2006,31(10):868-870(祝江汉,李曦,毛赤龙,等.多卫星区域观测任务的侧摆方案优化方法研究[J].武汉大学学报·信息科学版,2006,31(10):868-870)
[3] Lemalt^re M,Verfaillie G,Jouhaud F,et al.Selecting and Scheduling Observations of Agile Satellites[J].Aerospace Science and Technology,2002,6(5):367-381
[4] Ruan Qiming,Tan Yuejin,Li Jufang,et al.Research on Segmenting and Selecting of Area Targets[J].Surveying Science,2006,31(1):98-100(阮启明,谭跃进,李菊芳,等.对地观测卫星的区域目标分割与优选问题研究[J],测绘科学,2006,31(1):98-100)
[5] Zhang Dengyi,Guo Lei,Wang Qian,et al.An Improved Single-Orbit Scheduling Method for Agile Imaging Satellite Towards Area Target[J].Geomatics and Information Science of Wuhan University,2014,39(8):901-905,922(章登义,郭雷,王骞,等.一种面向区域目标的敏捷成像卫星单轨调度方法[J].武汉大学学报·信息科学版,2014,39(8):901-905,922)
[6] Shen Xin.Research on Key Technologies of Orbit Design for Optical Remote Sensing Satellite[D].Wuhan:Wuhan University,2012(沈欣.光学遥感卫星轨道设计若干关键技术研究[D].武汉:武汉大学,2012)
[7] Bala R V.A Generic Solution to Polygon Clipping[J].Communications of the ACM,1992,35(7):56-63
[8] Agoston M K.Computer Graphics and Geometric Modeling:Implementation and Algorithms[M].Berlin:Springer,2005
[9] Holland J H.Adaptation in Natural and Artificial Systems[M].Michigan:University of Michigan Press,1975
[10]Srinivas M,Patnaik L M.Adaptive Probabilities of Crossover and Mutation in Genetic Algorithms[J].IEEE Transactions on Systems,Man,and Cybernetics,2002,24(4):656-667
[11]Kuang Hangyu,Jin Jing,Su Yong.Improving Crossover and Mutation for Adaptive Genetic Algorithm[J].Computer Engineering and Applications,2006,42(12):93-96(邝航宇,金晶,苏勇.自适应遗传算法交叉变异算子的改进[J].计算机工程与应用,2006,42(12):93-96)
[12]Ren Ziwu,San Ye.Improved Adaptive Genetic Algorithm and Its Application Research in Parameter Identification[J].Journal of System Simulation,2006,18(1):41-43(任子武,伞冶.自适应遗传算法的改进及在系统辨识中应用研究[J].系统仿真学报,2006,18(1):41-43)
[13]Shi Shan,Li Qingfu,Wang Xinghua.Optimum Design of Brushless DC Motor Based on Adaptive Genetic Algorithm[J].Journal of Xi’an Jiaotong University,2002,36(12):1 215-1 218(石山,励庆孚,王兴华.基于自适应遗传算法的无刷直流电机的优化设计[J].西安交通大学学报,2002,36(12):1 215-1 218)
[14] Mazarico E,Rowlands D,Neumann G A,et al.Orbit Determination of the Lunar Reconnaissance Orbiter[J].Journal of Geodesy,2012,86(3):193-207
[15]Zheng Yongchun,Zou Yongliao,Fu Xiaohui.LRO and LCROSS Missions:Overview and Enlightenment for Future Lunar Exploration[J].Spacecraft Engineering,2011,20(4):117-129(郑永春,邹永廖,付晓辉.LRO和LCROSS探月计划:科学探测的分析与启示[J].航天器工程,2011,20(4):117-129)