CAJ | 학술논문

考虑到GEO卫星实际的运动特点,将常速度模型作为状态方程,用Kalman滤波法对GEO卫星进行运动学定轨.针对无系统误差和有系统误差的情形分别使用单向滤波和双向滤波的方法,其中双向滤波的思想是:先用正向滤波估计系统误差参数,然后将其作为初始值进行反向滤波.模拟算例表明:观测值仅含偶然误差时,单向Kalman滤波法定轨具有较高的精度;但当观测值中含有系统误差时,定轨精度急剧下降,顾及系统误差参数的单向Kalman滤波可在一定程度上削弱系统误差的影响,利用双向Kalman滤波法可进一步削弱系统误差的影响,提高定轨精度.算例还表明Kalman滤波法定轨可较为精确地估计出GEO卫星的运行速度.
고필도GEO위성실제적운동특점,장상속도모형작위상태방정,용Kalman려파법대GEO위성진행운동학정궤.침대무계통오차화유계통오차적정형분별사용단향려파화쌍향려파적방법,기중쌍향려파적사상시:선용정향려파고계계통오차삼수,연후장기작위초시치진행반향려파.모의산례표명:관측치부함우연오차시,단향Kalman려파법정궤구유교고적정도;단당관측치중함유계통오차시,정궤정도급극하강,고급계통오차삼수적단향Kalman려파가재일정정도상삭약계통오차적영향,이용쌍향Kalman려파법가진일보삭약계통오차적영향,제고정궤정도.산례환표명Kalman려파법정궤가교위정학지고계출GEO위성적운행속도.
Considering the features of the motion of GEO( Geostationary Earth Orbit ) satellite, Kalman filtering by using constant velocity model as state equation is proposed. When there exists systematic errors, forward and backward filtering is used, and when not, forward filtering. And the idea behind forward and backward filtering is that, firstly, using forward filtering estimates systematic error parameters, then the values obtained are used to do backward filtering. The simulation results show when there exists only random errors in observations, the use of orbit determination by forward Kalman filtering has a relatively high accuracy, but once system errors are involved, the accuracy will decrease sharply. The forward Kalman filtering considering systematic error parameters can weaken the impacts of systematic errors to a certain degree; while the application of forward and backward Kalman filtering will further weaken the influences of systematic errors and improve the accuracy of orbit determination. The results also show that orbit determination by Kalman filtering can comparatively exactly estimate the running velocity of GEO satellite.