摘要
基于星光折射的自主导航系统结构简单、成本低廉,理论上能够实现对飞行器的高精度导航。但由于测量模型受大气参数不确定性的影响,使得该导航方法的精度及可靠性严重降低。根据飞行器处于低轨段的卫星导航数据,通过神经网络在线拟合星光折射模型,避免了大气参数不确定性的影响,提高了星光折射导航精度。通过仿真重点研究了星光折射模型的特点、拟合方法,并对拟合模型的精度进行了分析。
The autonomous navigation system based on starlight atmosphere refraction has simple structure and low cost.Using the system,the spacecraft can get high-precision navigation data.But the measurement model has some imprecise atmospheric parameter,which reduces the navigation precision and reliability seriously.The above effects can be avoided by nervous network fitting starlight atmosphere refraction model on line,using satellite navigation data,when the spacecraft is at low orbit.This method can improve the navigation precision based on starlight refraction.Through simulation,the characteristics of the starlight refraction model and the fitting method were researched,and the precision analysis of the fitting models were also made.
出处
《国防科技大学学报》
EI
CAS
CSCD
北大核心
2011年第1期7-10,共4页
Journal of National University of Defense Technology
基金
国家863高技术计划项目(51309060302)
关键词
自主导航
星光折射
神经网络
拟合
autonomous navigation
starlight refraction
nervous network
fitting