摘要
针对运载火箭上升段轨迹建模问题,采用自由节点样条模型描述轨迹变化规律,将轨迹确定中的参数估计转化为对样条函数系数估计,从而大量减少待估参数个数,有效提高参数估计精度。在此基础上,提出利用遗传算法优选测量元素的方法。在基本遗传算法框架下,通过对测量元素进行染色体编码、构造基于加权排序的适应值函数以及设计改进的比例选择算子,对整个测量元素组合空间进行充分搜索寻优。利用典型上升段轨迹和布站对该方法进行数值仿真,结果表明,本文提出的新方法比现有方法的位置确定精度提高了92.O%~94.4%;在均采用自由节点样条模型进行融合轨迹确定时,新方法比典型测元融合解算的位置确定精度也提高了16.4%~88.6%.
For the problem of trajectory modeling in ascent phase of launch vehicle, free-node spline model is proposed to represent the change of this trajectory. The trajectory parameter estimation is converted to spline function coefficient estimation for trajectory determination, thus effectively improving accuracy by reducing the number of estimated parameters. Furthermore, an algorithm for optimization of measurement elements is obtained to improve accuracy of the trajectory determination by using chromosome encoding of measurement elements, constructing fitness function based on weighted ranking and designing the improved proportion selecting operator in basic genetic algorithm frame. Then the combinatorial space of measurement elements is sufficiently searched for optimization. The results of simulation based on the classical trajectory of ascent phase and distribution of stations show that accuracy of ascent trajectory determination is effectively improved. Compared with traditional methods, position determination accuracy of this method is improved from 92.0% to 94.4%. In the case of using free-node spline model, the position determination accuracy is also enhanced to 16.4% 88.6%.
出处
《宇航学报》
EI
CAS
CSCD
北大核心
2015年第9期1018-1023,共6页
Journal of Astronautics
关键词
运载火箭
上升段
测元融合
遗传算法
Launch vehicle
Ascent phase
Measurement element fusion
Genetic algorithm