摘要
稀疏测向数据下的天基初轨确定具有重要的应用价值。针对地基Laplace和Gauss方法在天基稀疏测向初定轨中存在的不收敛和平凡解问题,提出了一种新的模型———双ρ迭代模型,研究了优化算法中的变尺度方法和遗传算法作为解算算法,最后进行了仿真。结果表明,双ρ迭代模型可以较好地解决地基方法在天基测向初定轨应用中的上述问题,利用变尺度法的双ρ迭代模型具有90%以上的解算成功率,且具有良好的解算速度和收敛性,而采用改进的遗传算法可以解算其余算例,二者结合使用可以达到较好的初定轨效果。
Model and algorithm for initial orbit determination based on sparse space-based angle measurements are discussed in this article. Above all, the double ρ iteration, a new model of space-based initial orbit determination, is put forward to remedy invalidations of the traditional ground Laplace and Gauss methods. Then, adjustable-scale algorithm and genetic algorithm are focused to solve the problem. The numerical simulations in the end show that the double ρ iteration model can overcome the draw-backs of the traditional ground methods and the adjustable-scale algorithm is able to solve more than 90% cases and the modified genetic algorithm is a potent supplement. The combination of two algorithms would be perfect.
出处
《宇航学报》
EI
CAS
CSCD
北大核心
2009年第3期870-876,共7页
Journal of Astronautics
关键词
天基测向
稀疏数据
初定轨
双ρ迭代模型
变尺度法
遗传算法
Space-based angle measurement
Sparse data
Initial orbit determination
Adjustable-scale algorithm
Double ρ iteration
Genetic algorithm
