考虑分布参数依赖的风险混合不确定性分析方法

在定量化风险评估中,针对变量分布参数存在依赖时的混合不确定性传播问题,提出一种考虑分布参数完全依赖、部分依赖以及独立传播情形的双层混合不确定性刻画与传播框架,内外层分布参数不确定性分别用概率分布与可能性分布刻画,采用蒙特卡罗模拟法与模糊扩展原则相结合的数值求解方法。针对认知不确定性分布参数依赖性,构建了统一的认知不确定性分布参数依赖性模型,并给出依赖性系数的概念。为实现认知不确定性分布参数独立性采样,设计了基于D-S证据理论与随机集相结合的不确定性传播算法,相比于概率刻画下的双层蒙特卡罗方法,计算代价有效降低。以某型氢氧发动机贮箱共底漏气率为算例,验证本文方法的有效性与可行性。     

Advanced ensemble modeling method for space object state prediction accounting for uncertainty in atmospheric density

For objects in the low Earth orbit region, uncertainty in atmospheric density estimation is an important source of orbit prediction error, which is critical for space traffic management activities such as the satellite conjunction analysis. This paper investigates the evolution of orbit error distribution in the presence of atmospheric density uncertainties, which are modeled using probabilistic machine learning techniques. The recently proposed “HASDM-ML,” “CHAMP-ML,” and “MSIS-UQ” machine learning models for density estimation (Licata and Mehta, 2022b; Licata et al., 2022b) are used in this work. The investigation is convoluted because of the spatial and temporal correlation of the atmospheric density values. We develop several Monte Carlo methods, each capturing a different spatiotemporal density correlation, to study the effects of density uncertainty on orbit uncertainty propagation. However, Monte Carlo analysis is computationally expensive, so a faster method based on the Kalman filtering technique for orbit uncertainty propagation is also explored. It is difficult to translate the uncertainty in atmospheric density to the uncertainty in orbital states under a standard extended Kalman filter or unscented Kalman filter framework. This work uses the so-called “consider covariance sigma point (CCSP)” filter that can account for the density uncertainties during orbit propagation. As a test-bed for validation purposes, a comparison between CCSP and Monte Carlo methods of orbit uncertainty propagation is carried out. Finally, using the HASDM-ML, CHAMP-ML, and MSIS-UQ density models, we propose an ensemble approach for orbit uncertainty quantification for four different space weather conditions.     

Analysis of the DORIS contributions to ITRF2008

In its function as an ITRS Combination Centre, DGFI is in charge with the computation of an ITRF2008 solution. The computation methodology of DGFI is based on the combination of datum-free normal equations (weekly or session data sets, respectively) of station positions and Earth orientation parameters (EOP) from the geodetic space techniques DORIS, GPS, SLR and VLBI. In this paper we focus on the DORIS part within the ITRF2008 computations. We present results obtained from the analysis of the DORIS time series for station positions, network translation and scale parameters, as well as for the terrestrial pole coordinates. The submissions to ITRF2008 benefit from improved analysis strategies of the seven contributing IDS analysis centres and from a combination of the weekly solutions of station positions and polar motion. The results show an improvement by a factor of two compared to past DORIS data submitted to ITRF2005, which has been evaluated by investigating the repeatabilities of position time series. The DORIS position time series were analysed w.r.t. discontinuities and other non-linear effects such as seasonal variations. About 40 discontinuities have been identified which have been compared with the results of an earlier study. Within the inter-technique combination we focus on the DORIS contribution to the integration of the different space geodetic observations and on a comparison of the geodetic local ties with the space geodetic solutions. Results are given for the 41 co-location sites between DORIS and GPS.     

Orbital error propagation considering atmospheric density uncertainty

Due to the influence of various errors, the orbital uncertainty propagation of artificial celestial objects while orbit prediction is required, especially in some applications such as conjunction analysis. In the orbital error propagation of artificial celestial objects in low Earth orbits (LEOs), atmospheric density uncertainty is one of the important factors that require special attention. In this paper, on the basis of considering the uncertainties of position and velocity, the atmospheric density uncertainty is also taken into account to further investigate the orbital error propagation of artificial celestial objects in LEOs. Artificial intelligence algorithms are introduced, the MC Dropout neural network and the heteroscedastic loss function are used to realize the correction of the empirical atmospheric density model, as well as to provide the quantification of model uncertainty and input uncertainty for the corrected atmospheric densities. It is shown that the neural network we built achieves good results in atmospheric density correction, and the uncertainty quantization obtained from the neural network is also reasonable. Moreover, using the Gaussian mixture model - unscented transform (GMM-UT) method, the atmospheric density uncertainty is taken into account in the orbital uncertainty propagation, by adding a sampled random term to the corrected atmospheric density when calculating atmospheric density. The feasibility of the GMM-UT method considering atmospheric density uncertainty is proved by the further comparison of abundant sampling points and GMM-UT results (with and without considering atmospheric density uncertainty).     

IMU／GPS组合导航中坐标变换问题的研究

在导航定位时,不同的情况下需要的参数不同,而不同坐标系之间的坐标变换一直是导航算法的基石。讨论了地球坐标系内,大地坐标与直角坐标之间进行相互变换的算法和精度,及其对实现高效的组合导航算法的意义。给出了两种坐标变换算法及其推导过程,通过实例数据进行了仿真,并对结果进行了比较和讨论,分析了两种坐标变换方法的特点和应用的可行性。     

Accurate estimation of relative atmospheric density error on the example of uncertain geomagnetic activity information

Errors in neutral atmospheric density are the dominant contributor to unrealistic orbital state-vector covariances in low Earth orbits (LEO). Density uncertainty is caused by model-uncertainty at spatial scales below and within the model resolution, as well as input-uncertainty of the environmental parameters supplied to the semi-empirical atmospheric model.The paper at hand provides multiple contributions. First, analytic equations are derived to estimate the relative density error due to an input parameter uncertainty in any of the environmental parameters supplied to the model. Second, it is shown on the example of uncertain geomagnetic activity information, how to compute the required inputs to facilitate the accurate estimation of the relative density error.A clamped cubic splining approach for the conversion from geomagnetic amplitude (ap) to the kp index is postulated to perform this uncertainty propagation, as other algorithms were found unsuitable for this task. Results of numerical simulations with three popular semi-empirical models are provided to validate the set of derived equations. It is found that geomagnetic input uncertainty is especially important to consider in case of low global geomagnetic activity. The findings seamlessly integrate with prior work by the authors to perform density-uncertainty considering orbit estimation.     

On uncertainties in carbon flux modelling and remotely sensed data assimilation: The Brasschaat pixel case

Uncertainty on carbon fluxes is determined by the uncertainties of ecosystem model structure, data and model parameter uncertainties and the temporal and spatial inaccuracy of the input data retrieval. The objective of this paper is to understand the error propagation and uncertainty of evaporative fraction (EF), soil moisture content (SMC) and water limited net ecosystem productivity (NEP). In this respect, C-Fix and spaceborne remote sensing are used for the ‘Brasschaat’ pixel. A simple model based on error theory and a Monte-Carlo approach are used. Different error scenarios are implemented to assess input uncertainty on EF, SMC and NEP as estimated with C-Fix.     

适用于时变不确定系统的并行模型自适应估计

摘要： 针对受到潜在模型不确定性影响的系统,设计一种并行模型自适应估计(PMAE)算法.以往基于不确定性系统模型设计的滤波算法,在模型精确的情况下,性能往往不及传统卡尔曼滤波（KF）.为了解决该问题,设计基于多个并行滤波器的自适应状态估计算法,其中一个滤波器为KF,用于在未出现模型不确定性的情况下,对系统进行最优状态估计;另一个滤波器为扩维卡尔曼滤波（AKF）,用于在出现模型不确定性的情况下,对不确定性模型参数进行辨识.以空间目标监视为例,分析算法的性能.仿真结果表明,利用PMAE算法能够自适应地对两个并行滤波器进行切换和折衷,从而有效应对模型中存在不确定性和不存在不确定性两种情况.     

利用OH夜气辉反演原子氧数密度时输入参数的不确定度对反演结果的影响

借助OH夜气辉辐射的光化学模式,由OH夜气辉辐射反演中间层-低热层区域的原子氧数密度时,输入参数的不确定性将导致反演得到的原子氧数密度具有不确定性.以在sudden death猝灭模式下通过OH(8-3)振动带体辐射率反演原子氧数密度为例,分别研究了大气参数和OH气辉辐射率的不确定度引起的反演不确定度、化学反应速率常数的不确定度引起的反演不确定度,以及所有输入参数的不确定度共同引起的反演不确定度,找出其不确定度对反演结果影响最大的参数.结果表明,三种反演不确定度均随着高度的升高而增大,温度和体辐射率的不确定度对第一种反演不确定度的贡献最大,反应速率常数b(8)和A(8-3)、的不确定度对第二种反演不确定度的贡献最大.     

Impact of Jason-2/T2L2 Ultra-Stable-Oscillator Frequency Model on DORIS stations coordinates and Earth Orientation Parameters

Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) is a tracking technique based on a one-way ground to space Doppler link. For Low Earth Orbit (LEO) satellites, DORIS shows a robust capability in terms of data coverage and availability, due to a wide and well-distributed ground network, where data are made available by the International Doris Service (IDS). However, systematic errors remain in the DORIS data, such as instabilities of the on-board clock due to radiation encountered in space, which limit the accurate determination of station positions.The DORIS on-board clock frequency stability is degraded by the increased radiation found in the region of the South Atlantic Anomaly (SAA) and has been shown to degrade station position estimation. This paper introduces a new model correction to the DORIS data for the frequency of the Jason-2 Ultra Stable Oscillator (USO), derived from the Time Transfer by Laser Link (T2L2) experiment (Belli and Exertier, 2018). We show that a multi-satellite DORIS solution including this T2L2-corrected data applied to the frequency modelling for The DORIS data, improves the estimation of station coordinates. We show the tie residuals with respect to collocated GPS stations are improved by several millimeters. We also demonstrate that the 117-day (Jason-2) draconitic signal in the geophysical parameters is reduced, implying that the origin of this signal is not just solar radiation pressure mis-modeling, but also radiation-induced clock perturbations on the Jason-2 DORIS Ultra-Stable-Oscillator (USO). Finally we demonstrate through comparisons with the International Earth Rotations and Reference Systems Service (IERS) C04 series for Earth Orientation Parameters (EOP), that the estimation of EOP is improved in both a Jason-2 DORIS-only and a multi-satellite DORIS solution for EOP.     

复合材料点阵夹芯梁振动特性区间分析与优化

考虑到复合材料的分散性,研究了复合材料点阵夹芯梁的自由振动特性.将不确定参数用区间向量进行定量化,提出高精度的含不确定参数复合材料点阵夹芯梁固有频率的配点型区间分析方法,该方法无需不确定参数的概率信息,只需明确不确定参数所在范围界限,进而实现复合材料点阵夹芯梁结构的不确定优化.该方法为解决非线性现象突出的新型复合材料设计等复杂问题提供了一个可行途径.与概率方法相比,区间分析方法的结果表明该方法是可行的.与确定性优化方法相比,区间优化方法在复合材料结构优化领域能够充分考虑结构潜在不确定性带来的不利影响,工程指导意义更为明显.     

Impact of loading effects on determination of the International Terrestrial Reference Frame

The International Terrestrial Reference Frame (ITRF), as a realization of the International Terrestrial Reference System (ITRS), is represented by a set of station positions and linear velocities. They are intended to be used as regularized coordinates to which some corrections should be added to access instantaneous coordinates. The latest ITRS realization is the ITRF2005, which has integrated time series of station positions to form long-term solutions for the four space geodetic techniques. Currently, a purely linear model is used to parameterize station displacements in the estimation process, plus occasional discontinuities in case of earthquakes or equipment changes. However the input data have been derived without applying surface loading models and so surface loading effects are supposed to be embedded in the coordinates as measured quantities. We evaluate the effect of applying a posteriori loading corrections, which include the effect of atmospheric, non-tidal ocean, and continental water loading, to time series of positions estimated from Satellite Laser Ranging (SLR), Very Long Baseline Interferometry (VLBI), and Global Positioning System (GPS) data. We notice that they reduce about 50% or more of the annual signals in the translation and scale parameter time series of the SLR and VLBI techniques, except in SLR Z translation. In general, the estimated secular frame definition is negligibly affected and estimated positions and velocities are not significantly modified for stations that have accumulated a large number of observations. A multi-technique combination of such derived frames allows concluding that, for some cases, loading model corrections might degrade co-located station coordinates almost as much as they benefit them. However, most significant improvement of the estimated secular coordinates is observed for stations with less than 100 estimated positions as demonstrated with a multi-technique combination.     

噪声源校准方法及不确定度分析

噪声系数测量的一个关键指标就是测量不确定度,测量时所用的噪声源是引起噪声系数测量不确定度的一个明显因素。噪声源的精确校准可以有效地降低噪声系数的测量不确定度,因此它是获得高质量的噪声系数测量的关键因素。介绍了两种对微波和毫米波噪声源超噪比进行校准的方法,分别是Y因子法和增益法,并全面分析了引起校准不确定度的因素。     

飞行控制律评估与确认的μ分析方法

针对目前应用的网格法在实际使用中的不足,将μ分析方法应用到飞行控制律 的评估与确认中.以某型战斗机及为其设计的鲁棒飞行控制律为研究对象,采用相应的稳定 性准则,利用线性分式变换形式,考虑各种已知的不确定参数摄动,用μ分析方法实现了对 该准则的评估与确认.与传统网格法相比,基于μ分析的方法具有两个明显的优点,一是网 格间的点可以得到评估,二是不存在网格法的"维数灾"问题,从而提高了评估的可靠性和 效率.     

Adaptive sliding mode control of spacecraft attitude-orbit dynamics on SE(3)

In this paper, to solve the problem of parameters uncertainty in spacecraft tracking control, an adaptive controller based on sliding mode is proposed for the relative spacecraft attitude-orbit dynamics on the Lie group SE(3). The dynamic equations of relative attitude orbit error for two spacecraft are established in the framework of Lie group SE(3). Considering the uncertainty of spacecraft parameters, a formal decomposition of known and unknown parameters, the state variables and control variables is firstly made in the original system. An online estimator is designed to evaluate the unknown parameters. A sliding mode controller is developed to actuate the spacecraft to track the target spacecraft. Then a Lyapunov function of tracking error and parameters estimated error is designed to prove the stability of the closed-loop system. Finally, the simulation results and analysis are presented to verify the effectiveness and feasibility of the proposed method.     

基于测量数据的不确定性结构分析的模糊理论

针对不确定性结构力学问题,提出了基于测量数据的模糊分析方法.该方法利用差值因子构造了不确定参数的隶属度函数,对不确定参数的有限个分散数据进行不确定性描述和定量化处理,估计出其真值估计和区间估计,将其运用到不确定性结构力学问题的模糊有限元分析中,以求得结构的不确定性响应.最后以十杆桁架结构为例,运用该方法对结构的不确定响应进行了分析,仿真结果验证了该方法的有效性.     

压力传感器动态特性参数不确定度评定

压力传感器动态特性参数的不确定度是表征其动态测量性能的重要指标。提出了一种压力传感器动态特性参数的不确定度评定方法。首先,使用激波管动态校准系统产生阶跃压力信号激励压力传感器,得到传感器的输出信号;其次,采用基于经验模态分解（EMD）的传感器输出信号预处理方法,减小动态校准过程中噪声的影响;然后,根据传感器的输入输出信号,采用自适应最小二乘法建立压力传感器的数学模型,进而得到其时频域动态特性参数;最后,针对重复校准实验得到的动态特性参数序列的小样本特点,采用自助法计算参数的扩展不确定度和相对不确定度。采用激波管系统对压力传感器进行多次重复动态校准实验,计算时频域动态特性参数的不确定度,并与现有方法进行对比。实验结果表明:本文方法可以弥补贝塞尔法在处理小样本量数据中的不足,且与蒙特卡罗法的不确定度评定结果相对误差小于10%,说明本文方法可以有效地评定压力传感器动态特性参数的不确定度。分析时频域动态特性参数的相对不确定度得到传感器的工作频带和超调量受噪声的影响较大,为动态校准实验条件的改善提供了重要依据。      

Optimal H∞ robust output feedback control for satellite formation in arbitrary elliptical reference orbits

A two degree-of-freedom signal-based optimal H_∞ robust output feedback controller is designed for satellite formation in an arbitrary elliptical reference orbit. Based on high-fidelity linearized dynamics of relative motion, uncertainties introduced by non-zero eccentricity and gravitational J2 perturbation are separated to construct a robust control model. Furthermore, a distributed robust control model is derived by modifying the perturbed robust control model of each satellite with the eigenvalues of the Laplacian matrix of the communication graph, which represent uncertainty in the communication topology. A signal-based optimal H_∞ robust controller is then designed primarily. Considering that the uncertainties involved in the distributed robust control model have a completely diagonal structure, the corresponding analyses are made through structured singular value theory to reduce the conservativeness. Based on simulation results, further designs including increasing the degrees of freedom of the controller, modifying the performance and control weighted functions, adding a post high-pass filter according to the dynamic characteristics, and reducing the control model are made to improve the control performance. Nonlinear simulations demonstrate that the resultant optimal H_∞ robust output feedback controller satisfies the robust performance requirements under uncertainties caused by non-zero eccentricity, J2 perturbation, and varying communication topology, and that 5 m accuracy in terms of stable desired formation configuration can be achieved by the presented optimal H_∞ robust controller. In addition to considering the widely discussed uncertainties caused by the orbit of each satellite in a formation, the optimal H_∞ robust output feedback control model presented in the current work considers the uncertainties caused by varying communication topology in the satellite formation that works in a cooperative way. Other new improvements include adopting a new method to more accurately describe and analyze the effects of the higher-order J2 perturbation, combining all the uncertainties into a diagonal structure, and utilizing a structured singular value to synthesize and analyze the controller.     

Simulation of long-term rotational dynamics of large space debris: A TOPEX/Poseidon case study

Accurate knowledge of the rotational dynamics of a large space debris is crucial for space situational awareness (SSA), whether it be for accurate orbital predictions needed for satellite conjunction analyses or for the success of an eventual active debris removal mission charged with stabilization, capture and removal of debris from orbit. In this light, the attitude dynamics of an inoperative satellite of great interest to the space debris community, the joint French and American spacecraft TOPEX/Poseidon, is explored. A comparison of simulation results with observations obtained from high-frequency satellite range measurements is made, showing that the spacecraft is currently spinning about its minor principal axis in a stable manner. Predictions of the evolution of its attitude motion to 2030 are presented, emphasizing the uncertainty on those estimates due to internal energy dissipation, which could cause a change of its spin state in the future. The effect of solar radiation pressure and the eddy-current torque are investigated in detail, and insights into some of the satellite’s missing properties are provided. These results are obtained using a novel, open-source, coupled orbit-attitude propagation software, the Debris SPin/Orbit Simulation Environment (D-SPOSE), whose primary goal is the study of the long-term evolution of the attitude dynamics of large space debris.     

大型捆绑运载火箭反步自适应增广控制研究

针对大型捆绑火箭空间模态参数不确定性较大的特点,建立了大型捆绑运载火箭姿态动力学模型,提出了基于反步的自适应增广控制方法,设计了反步控制律,分析了自适应增广控制的机理,并针对弹性参数不确定性进行了仿真。理论分析和仿真结果表明,所提出的基于反步的自适应增广控制对于空间模态参数的不确定性具有很强的适应性。