基于双频GPS观测的简化动力学最小二乘批处理精密定轨

星载双频GPS载波相位和伪距观测量已成为低轨卫星获取精确三维位置和速度信息的主要方式. 本文以非差消电离载波相位和伪距组合作为观测量,应用简化动力学最小二乘批处理方法进行地球低轨卫星的精密定轨,并给出完整定轨流程. 采用逐段常量的经验加速度对动力学模型误差进行补偿,描述了经验加速度敏感矩阵及稀疏带状矩阵求逆的有效计算方法. 利用GRACE-A卫星GPS观测数据对定轨位置精度进行分析,结果显示,三维位置定轨精度优于5cm,经验加速度在径向、切向和法向上的补偿水平不超过40nm·s-2,大气阻力系数和辐射光压系数的估计值符合物理实际,星载接收机钟差大致呈线性并具有短周期小波动.      

星载GPS几何法实时定轨有关问题的研究

首先讨论了星载GPS几何法实时定轨的绝对定位方法和各种差分技术。由于伪距差技术能克服GPS卫星的星历误差、卫星钟误差，特别是SA误差的影响，而且实现难度不大，所以应用它来实时定轨。实测数据的处理表明，它能明显提高定轨的精度。然后分析了星载GPS所受扰动影响的情况，对应用抗差估计削弱GPS卫星信号扰动的影响进行了试验，试验的结果说明抗差估计能进一步提高星载GPS几何法定轨的精度。     

导航卫星的地面站定轨算法

导航星座轨道的长期保持是星座导航系统运营管理的重要组成部分,而现有的导航卫星地面定轨算法又存在精度不高或计算量大不适合工程应用的问题。为此,研究了单向、被动测量模式的导航卫星地面定轨算法。基于单向伪距观测,将导航卫星钟差参数作为状态量,推导了滤波算法的状态方程、测量方程,并最终建立了滤波器模型。以不同轨道面的4颗GPS导航卫星为例进行了2天的仿真试验,考虑卫星的可见性仿真中加入了测量中断,并设计在测量恢复后重启滤波算法。仿真结果表明,4颗卫星的轨道位置估计精度可以达到米级,钟差随机偏差的估计精度可以达到纳秒级,并且在滤波中断后重启滤波器,仍然可以达到此估计精度,表明此定轨算法具有收敛性和稳定性。     

精密GPS卫星钟差的改正和应用

分析了GPS卫生钟差的变化特性，探讨了利用GPS地面跟踪站的观测数据估算GPS卫星钟差的可行性，建立了相应的算法和软件系统，并把由地面跟踪站的实测数据估算的卫星钟差用于星载GPS定轨计算，得到优于1m的定轨精度。     

基于单频星载GPS数据的低轨卫星精密定轨

为满足搭载单频GPS接收机低轨卫星的精密定轨需求以及深化单频定轨研究,文中解决了单频星载GPS数据的周跳探测问题,并利用“海洋二号”（HY-2A）卫星及“资源三号”（ZY-3）卫星的单频星载GPS实测数据采用两种方法确定了二者的简化动力学轨道,并通过观测值残差分析、与双频精密轨道比较、激光测卫数据检核等方法对所得轨道精度进行评定。结果表明,在不考虑电离层延迟影响的情况下,HY-2A卫星定轨精度为2~3dm,ZY-3卫星为1m左右;而采用半和改正组合消除电离层延迟一阶项影响后,二者定轨精度均显著提高,HY-2A卫星三维精度提高至1dm左右,ZY-3卫星提高至1~2dm。文章的研究成果表明,搭载单频GPS接收机的低轨卫星也可获得厘米级的定轨精度。     

星载GPS低轨卫星几何法精密定轨研究

本文讨论了星载ＧＰＳ接收机为单频情形的代轨卫星几何法定轨,包括载波一相对定轨法和动态网定轨法,并利用Ｔｏｐｅｘ／Ｐｏｓｅｉｄｏｎ卫星星载ＧＰＳ实测数据中Ｌ１载波相位观测值进行验证,结果表明,载波相位相对定轨精度与地面基准站的观测质量有关,其三轨道位置精度为分米级;载波相位动态风定轨精度介于各基准站皮相位相对定轨之间,它相当于在各基准站相对定轨之间加权均衡,而且提高了定轨的可靠性。     

基于自适应滤波的编队卫星实时相对定轨

提出基于自适应滤波的编队卫星实时相对定轨算法,利用2005-12-09—10两颗GRACE（Gravity Recovery and Climate Experiment）卫星的GPS（Global Positioning System）实测数据进行实时相对定轨试验计算,采用JPL（Jet Propulsion Laboratory）轨道对试验结果外部检核,结果表明:①自适应滤波相对定轨通过自适应因子,可以较好地平衡编队卫星的观测信息和相对动力学信息,其相对定轨结果精度优于Kalman滤波相对定轨结果;②自适应滤波相对定轨结果随着星间基线缩短而精度提高;③两颗GRACE卫星采用单频伪距和广播星历进行自适应滤波相对定轨,可以得到精度优于6cm的星间基线。     

基于固定模糊度PPP的低轨卫星实时精密定轨

传统动力学定轨法受制于动力学模型精度，传统几何定轨法精度受限，只能达到亚米级，而基于精密单点定位（PPP）模式的几何定轨法一般采用浮点解，定轨精度及可靠性较基于双差模式的相对定位较差。为提高PPP模式低轨定轨的定位性能，利用中国区域内外的IGS测站计算出当前所有卫星的宽巷和窄巷相位小数偏差产品，对经过中国大陆区域上空的国产低轨卫星海洋二号（HY-2）和资源三号 (ZY-3) 卫星进行固定模糊度PPP的定轨解算，与事后精密轨道结果进行比较，分析其外符合精度。结果表明：仅利用约10min弧段的HY-2和ZY-3卫星数据，切向与径向的定轨精度可达2cm左右，法向为5cm左右，较浮点解定轨精度大幅提升。基于固定模糊度PPP的定轨方法能够满足厘米级的实时精密定轨。     

一种新的星载GPS定轨滤波算法

针对传统EKF(Extended Kalman Filtering)算法应用于星载GPS(Global Positioning System)低轨卫星定轨时系统噪声方差初值不易确定的问题,提出了一种新的定轨滤波算法.该算法在非线性方程线性化过程中,在前一时刻滤波估值点进行线性化,从而得到扰动方程,并将该扰动方程引入到传统EKF进行滤波处理.该算法与传统EKF分别应用在星载GPS低轨卫星的定轨中,通过比较,结果表明改进的算法在一定程度上抑制了由于系统噪声方差阵选取偏差较大而引起的滤波发散现象,且对于系统噪声方差的初值选取有较强的鲁棒性.      

基于联合滤波器的高精度卫星定姿系统设计

设计了由陀螺、GPS姿态敏感器、红外地平仪和太阳敏感器构成的太阳同步极轨卫星姿态确定系统。提出联邦滤波器结构和算法,推导了各子系统的量测方程和姿态确定系统的误差状态方程。为规避对量测值进行非相关处理,采用减小GPS姿态敏感器输出的姿态滤波值作为系统滤波器量测值的频率的方法。仿真结果表明,采用联邦滤波器对多敏感器卫星姿态确定系统进行信息融合,具有计算量小、精度高、可靠性好等优点。     

Kalman滤波估算电离层延迟的一种优化方法

频间偏差（Inter Frequency Bias，IFB）通常会给电离层延迟的解算带来误差.目前从电离层延迟中消除频间偏差的方法是基于GPS双频观测数据建立垂直电离层模型，利用卡尔曼滤波实时估算电离层模型系数和频间偏差.然而滤波过程中的测量噪声协方差矩阵没有考虑系统观测量之间的相关性，这会导致滤波模型不准确，进而影响最后求解的电离层延迟的准确性.本文选取了美国19个参考站的GPS双频观测数据，利用卡尔曼滤波实时估算电离层模型系数以及频间偏差.在滤波过程中，通过将先验频间偏差的估计方差引入测量噪声方差，实现对测量噪声协方差矩阵的优化.计算结果表明，优化后得到的卫星频间偏差与欧洲定轨中心（Center for Orbit Determination in Europe，CODE）得到的频间偏差更接近.将优化后的电离层延迟代入伪距解算，得到的位置误差的标准差在东向和天顶向分别下降了12.5%和15.4%，天顶向误差平均值下降了17.6%，定位精度得到提高.      

星载GPS观测数据的模拟研究

重点分析了星载GPS观测值模拟的原理、数学模型等，并用模拟软件模拟了CHAMP卫星的星载GPS观测值情况．结果表明，根据本文提供模拟方法所模拟的CHAMP星载GPS观测值，与实测值相比，无论是在大小还是观测噪声水平上都很接近，因此能满足不同层次人员对星载GPS模拟观测值的需要．     

Estimation of differential code biases with Jason-2/3 onboard GPS observations

With the continuous deployment of Low Earth Orbit (LEO) satellites, the estimation of differential code biases (DCBs) based on GNSS observations from LEO has gained increasing attention. Previous studies on LEO-based DCB estimation are usually using the spherical symmetry ionosphere assumption (SSIA), in which a uniform electron density is assumed in a thick shell. In this study, we propose an approach (named the SHLEO method) to simultaneously estimate the satellite and LEO onboard receiver DCBs by modeling the distribution of the global plasmaspheric total electron content (PTEC) above the satellite orbit with a spherical harmonic (SH) function. Compared to the commonly used SSIA method, the SHLEO model improves the GPS satellite DCB estimation accuracy by 13.46% and the stability by 22.34%, respectively. Compared to the GPS satellite DCBs estimated based on the Jason-3-only observations, the accuracy and monthly stability of the satellite DCBs can be improved by 14.42% and 26.8% when both Jason-2 and Jason-3 onboard observations are jointly processed. Compared with the Jason-2 solutions, the GPS satellite DCB estimates based on the fusion of Jason-2 and Jason-3 observations have an improved consistency of better than 18.26% and 9.71% with the products provided by the Center for Orbit Determination in Europe (CODE) and Chinese Academy of Sciences (CAS). Taking the DCB products provided by the German Aerospace Center (DLR) as references, there is no improvement in accuracy of the GPS satellite DCB estimates based on the fusion of Jason-2 and Jason-3 observations than the Jason-2 solutions alone. A periodic variation is found in the time series of both the Jason-3 and Jason-2 onboard receiver DCB estimates. Preliminary analysis of the PTEC distribution based on the estimated SH coefficients are also presented.     

A variational Bayesian-based robust adaptive filtering for precise point positioning using undifferenced and uncombined observations

In the application of precise point positioning (PPP), especially in the dynamic mode, the classical Kalman filter (KF) usually produces a large number of estimation errors or diverges when there are gross errors in the observation data or unexpected turbulences occur in target motion state or both of them. For such problem, a variational Bayesian (VB)-based robust adaptive Kalman filtering (VB-RAKF) is proposed in this paper. This filter introduces a classification robust equivalent weight function to resist observation gross error and the inverse Wishart prior to model inaccurate process noise covariance matrix (PNCM). To improve the instantaneous accuracy of state estimation, the VB approach is used to obtain better estimations of inaccurate PNCM. Several sets of observation data collected by IGS reference stations and vehicles are employed to check the robustness and positioning accuracy of the VB-RAKF model. The results show that the VB-RAKF algorithm is more robust than the KF, and can effectively resist the gross error in observation data and control state disturbance. In the IGS reference station tests, when compared to the KF, the static positioning accuracies of the VB-RAKF in the north, east and up directions are improved by 13%, 8% and 22%, respectively, and the simulated dynamic positioning accuracies of the VB-RAKF in the north, east and up directions are improved by 19%, 9% and 21%, respectively. The in-vehicle dynamic test verifies that the VB-RAKF outperforms the KF, and shows that the VB-RAKF has better performance than the KF when dealing with observation data which has obvious gross errors, and similar performance as the KF when gross errors are small.     

抗差自适应滤波在低轨飞行器INS/CNS/GNSS 组合导航中的应用

低轨飞行器对导航系统的稳定性要求较高,采用标准卡尔曼滤波的组合导航系统在异常扰动情况下会产生较大误差,严重影响低轨飞行器导航精度.在此前提下提出将抗差自适应滤波用于低轨飞行器导航系统,并基于该滤波器设计INS/CNS/GNSS组合导航.通过仿真实验对比验证抗差自适应滤波的有效性.     

The multi-source data fusion global ionospheric modeling software—IonoGim

We introduce a new global ionospheric modeling software—IonoGim, using ground-based GNSS data, the altimetry satellite and LEO (Low Earth Orbit) occultation data to establish the global ionospheric model. The software is programmed by C++ with fast computing speed and highly automatic degree, it is especially suitable for automatic ionosphere modeling. The global ionospheric model and DCBs obtained from IonoGim were compared with the CODE (Center for Orbit Determination in Europe) to verify its accuracy and reliability. The results show that IonoGim and CODE have good agreement with small difference, indicating that IonoGim owns high accuracy and reliability, and can be fully applicable for high-precision ionospheric research. In addition, through comparison between only using ground-based GNSS observations and multi-source data model, it can be demonstrated that the space-based ionospheric data effectively improve the model precision in marine areas where the ground-based GNSS tracking station lacks.     

A genetic algorithm for Initial Orbit Determination from a too short arc optical observation

Optical observations constitute a source of angular measurements of a satellite pass. Commonly, these observations have short durations with respect to the satellite orbit period. As a consequence, the use of classical orbit determination algorithms, as Laplace, Gauss or Escobal methods, give very poor results. The present work faces with the problem of estimating the orbital parameters of an orbiting object using its optical streak acquired by a telescope or a high accuracy camera. In the paper a new technique is developed for the Initial Orbit Determination from optical data by exploiting the genetic algorithms. The algorithm works without restrictions on the observer location. A recent challenging problem is the Initial Orbit Determination with space-based observations. This work focuses on the problem of determinating the orbital parameters of a satellite from an orbiting observer in LEO, using short time observations. We present the results based on a simulation with the observer on a sun-synchronous orbit with a single observation of just 60 s. Monte Carlo simulations are presented with different levels of sensor accuracy to show the reliability of the algorithm. The algorithm is able to yield a candidate solution for each observation. The coplanar case is analyzed and discussed as well.     

基于最小化新息协方差的修正SRCKF算法

目标跟踪过程中的模型误差会使得平方根容积卡尔曼滤波（SRCKF）性能下降,滤波精度降低;自适应滤波中的修正卡尔曼滤波（AKF）算法可以有效解决这一问题,但是难以应用到非线性滤波中。为了克服模型误差带来的不利影响,同时,进一步提高修正思想的应用范围,在SRCKF的基础上,基于最小化新息协方差准则推导了修正系数的向量形式,提出修正SRCKF(ASRCKF)算法。所提算法通过利用后期的测量数据,增加对测量值的信任度,从而达到对目标模型误差进行补偿的目的。仿真结果表明：与SRCKF和强跟踪SRCKF算法相比,所提ASRCKF算法能有效抑制模型误差,有着更优的滤波性能。     

Orbit determination performances using single- and double-differenced methods: SAC-C and KOMPSAT-2

In this paper, Global Positioning System-based (GPS) Orbit Determination (OD) for the KOrea-Multi-Purpose-SATellite (KOMPSAT)-2 using single- and double-differenced methods is studied. The requirement of KOMPSAT-2 orbit accuracy is to allow 1 m positioning error to generate 1-m panchromatic images. KOMPSAT-2 OD is computed using real on-board GPS data. However, the local time of the KOMPSAT-2 GPS receiver is not synchronized with the zero fractional seconds of the GPS time internally, and it continuously drifts according to the pseudorange epochs. In order to resolve this problem, an OD based on single-differenced GPS data from the KOMPSAT-2 uses the tagged time of the GPS receiver, and the accuracy of the OD result is assessed using the overlapping orbit solution between two adjacent days. The clock error of the GPS satellites in the KOMPSAT-2 single-differenced method is corrected using International GNSS Service (IGS) clock information at 5-min intervals. KOMPSAT-2 OD using both double- and single-differenced methods satisfies the requirement of 1-m accuracy in overlapping three dimensional orbit solutions. The results of the SAC-C OD compared with JPL’s POE (Precise Orbit Ephemeris) are also illustrated to demonstrate the implementation of the single- and double-differenced methods using a satellite that has independent orbit information available for validation.     

近似二阶扩展卡尔曼滤波方法研究

 在综合考虑计算量和估计精度的情况下,提出一种新的非线性滤波方法——近似二阶扩展卡尔曼滤波（AS-EKF）方法。该方法基于线性最小方差递推滤波框架,对均值的非线性变换采用二阶近似,其精度高于扩展卡尔曼滤波（EKF）采用的一阶近似。通过计算机仿真表明该滤波方法对非线性系统的滤波精度高于EKF,且计算量明显低于无迹滤波（UKF）,该方法适用于对估计精度和计算量都有所要求的非线性系统滤波器设计。