Two-Line Element(TLE)datasets are the only orbital data source of Earth-orbiting space objects for many civil users for their research and applications.The datasets have uneven qualities that may affect the reliabilit...Two-Line Element(TLE)datasets are the only orbital data source of Earth-orbiting space objects for many civil users for their research and applications.The datasets have uneven qualities that may affect the reliability of the propagated positions of space objects using a single TLE.The least squares approach to use multiple TLEs also suffers from the poor quality of some TLEs,and reliable error information cannot be available.This paper proposes a simplex algorithm to estimate an optimal TLE from multiple TLEs and obtain the uncertainty of each element.It is a derivative-free technique that can deal with various orbit types.Experiments have demonstrated that using the TLE estimated from the simplex method is more reliable,stable,and effective than those from the batch least squares method.As an application example,the optimal TLE and its uncertainty are used for predicting the fallen area,keeping the actual fallen site in the prediction areas.展开更多
For satellites in orbits,most perturbations can be well modeled;however the inaccuracy of the atmospheric density model remains the biggest error source in orbit determination and prediction.The commonly used empirica...For satellites in orbits,most perturbations can be well modeled;however the inaccuracy of the atmospheric density model remains the biggest error source in orbit determination and prediction.The commonly used empirical atmospheric density models,such as Jacchia,NRLMSISE,DTM,and Russian GOST,still have a relative error of about 10%-30%.Because of the uncertainty in the atmospheric density distribution,high accuracy estimation of the atmospheric density cannot be achieved using a deterministic model.A better way to improve the accuracy is to calibrate the model with updated measurements.Twoline element(TLE)sets provide accessible orbital data,which can be used in the model calibration.In this paper,an algorithm for calibrating the atmospheric density model is developed.First,the density distribution of the atmosphere is represented by a power series expansion whose coefficients are denoted by the spherical harmonic expansions.Then,the useful historical TLE data are selected.The ballistic coefficients of the objects are estimated using the BSTAR data in TLEs,and the parameterized model is calibrated by solving a nonlinear least squares problem.Simulation results show that the prediction error is reduced using the proposed calibration algorithm.展开更多
用于航天器轨道预报的热层密度模型普遍存在30%左右的误差,影响LEO卫星的精密轨道确定和载荷控制。基于低轨航天器平运动变化与大气密度的关系,使用GRACE(gravity recovery and climate experiment)卫星TLE数据反演2003、2007年沿轨大...用于航天器轨道预报的热层密度模型普遍存在30%左右的误差,影响LEO卫星的精密轨道确定和载荷控制。基于低轨航天器平运动变化与大气密度的关系,使用GRACE(gravity recovery and climate experiment)卫星TLE数据反演2003、2007年沿轨大气密度,通过比较反演值、模型值和实测值的关系分析误差产生原因,使用对数正态分布拟合密度比值。通过分析太阳辐射、地磁指数对大气密度变化的影响,提出一种基于空间环境指数的热层大气密度模型校正与预报方式。使用该方法对2003、2004、2007、2008年的MSIS86模型计算密度进行修正,将模型平均相对误差从33.33%~59.62%降低到11.55%~15.13%,太阳活动低年改进量是高年的1.5~2倍。对2009年经验模型结果进行预报校正,将预报误差降低36.49%,提高了模型精度。展开更多
基金supported by Chongqing Municipal Natural Science Foundation of General Program(CSTB2022NSCQMSX1093)the Science and Technology Research Program of Chongqing Municipal Education Commission(Grant No.KJQN202200701)China Postdoctoral Science Foundation(2021M703487).
文摘Two-Line Element(TLE)datasets are the only orbital data source of Earth-orbiting space objects for many civil users for their research and applications.The datasets have uneven qualities that may affect the reliability of the propagated positions of space objects using a single TLE.The least squares approach to use multiple TLEs also suffers from the poor quality of some TLEs,and reliable error information cannot be available.This paper proposes a simplex algorithm to estimate an optimal TLE from multiple TLEs and obtain the uncertainty of each element.It is a derivative-free technique that can deal with various orbit types.Experiments have demonstrated that using the TLE estimated from the simplex method is more reliable,stable,and effective than those from the batch least squares method.As an application example,the optimal TLE and its uncertainty are used for predicting the fallen area,keeping the actual fallen site in the prediction areas.
文摘For satellites in orbits,most perturbations can be well modeled;however the inaccuracy of the atmospheric density model remains the biggest error source in orbit determination and prediction.The commonly used empirical atmospheric density models,such as Jacchia,NRLMSISE,DTM,and Russian GOST,still have a relative error of about 10%-30%.Because of the uncertainty in the atmospheric density distribution,high accuracy estimation of the atmospheric density cannot be achieved using a deterministic model.A better way to improve the accuracy is to calibrate the model with updated measurements.Twoline element(TLE)sets provide accessible orbital data,which can be used in the model calibration.In this paper,an algorithm for calibrating the atmospheric density model is developed.First,the density distribution of the atmosphere is represented by a power series expansion whose coefficients are denoted by the spherical harmonic expansions.Then,the useful historical TLE data are selected.The ballistic coefficients of the objects are estimated using the BSTAR data in TLEs,and the parameterized model is calibrated by solving a nonlinear least squares problem.Simulation results show that the prediction error is reduced using the proposed calibration algorithm.
文摘用于航天器轨道预报的热层密度模型普遍存在30%左右的误差,影响LEO卫星的精密轨道确定和载荷控制。基于低轨航天器平运动变化与大气密度的关系,使用GRACE(gravity recovery and climate experiment)卫星TLE数据反演2003、2007年沿轨大气密度,通过比较反演值、模型值和实测值的关系分析误差产生原因,使用对数正态分布拟合密度比值。通过分析太阳辐射、地磁指数对大气密度变化的影响,提出一种基于空间环境指数的热层大气密度模型校正与预报方式。使用该方法对2003、2004、2007、2008年的MSIS86模型计算密度进行修正,将模型平均相对误差从33.33%~59.62%降低到11.55%~15.13%,太阳活动低年改进量是高年的1.5~2倍。对2009年经验模型结果进行预报校正,将预报误差降低36.49%,提高了模型精度。