摘要
由于卫星轨道观测数据中含有非线性影响因素,必然会降低定轨精度。在半参数回归模型的基础上,应用小波阈值去噪算法估计并消除观测数据中存在的非线性影响因素,提出了基于半参数回归模型的批处理确定卫星轨道的方法,以提高定轨精度;然后,在理论上证明了在测量数据存在非线性影响因素的情形下,基于半参数回归模型的批处理确定卫星轨道方法的定轨精度高于经典的批处理定轨精度;最后,对中低轨卫星应用批处理定轨进行了仿真。结果表明:基于半参数回归模型的批处理确定卫星轨道方法分离出观测数据中的白噪声和非线性影响因素,从而可以在观测数据中消除非线性影响因素,提高定轨的精度。
The nonlinear errors that exist inevitably in the observations of the satellite will cut down the accuracy of orbit determination. Based on the semi-parametric regression model, the observations were de-noising via wavelet threshold, and the nonlinear errors were estimated and removed from the observations. So the orbit determination method with batch processor based on semi-parametric regression model （ODBSPRM） was proposed to improve the accuracy of orbit determination. Then, the accuracy of ODBSPRM was proved to be higher than that of classical batch processor in theory on the situation that observations of satellite exists nonlinear errors. Finally, the simulation on orbit determination of low earth orbit satellite shows that ODBSPRM could separate the white noise and nonlinear errors, and improve the accuracy of orbit determination greatly.
出处
《宇航学报》
EI
CAS
CSCD
北大核心
2008年第6期1917-1921,1954,共6页
Journal of Astronautics
基金
国家自然科学基金(10573041)
关键词
批处理
轨道确定
半参数回归模型
非线性估计
小波阈值去噪
Batch processor
Orbit determination
Semi-parametric regression model
Non-linear systems estimation
Denoising via wavelet threshold
