基于最大似然估计的远紫外遥感反演电离层电子密度算法

原子氧135.6 nm夜气辉主要由氧离子O+与电子的辐射复合反应生成,一些星载远紫外遥感观测任务证实135.6 nm夜气辉可用于反演电离层电子密度。针对远紫外临边遥感观测反演电离层电子密度,分析了135.6 nm夜气辉辐射强度与电子密度之间的非线型前向模型,基于离散反演理论设计了从夜间135.6 nm临边观测数据反演电子密度高度分布的反演算法,算法应用最大似然估计通过迭代求解电离层参数的最佳拟合值。通过仿真计算了TIMED卫星上全球紫外成像仪GUVI观测的反演结果,验证了本反演算法的可行性。对GUVI的实际观测数据进行反演,获得了电子密度高度分布。通过与GUVI数据的电离层参数对比分析得出,本文建立的反演模型使N_mF₂被高估,同时使h_mF₂被低估。对于不同的太阳活动强度,N_mF₂和 h_mF₂的系统误差分别在10%和5%以内,能较精确地获得电离层参数。精确获得电离层电子密度信息对于提高空间天气预报及电离层模型的修正具有重要意义。      

地基Fabry-Perot中高层大气风速反演及误差分析

基于子午工程地基法布里-帕罗干涉仪（Fabry-Perot Interferometer,FPI）的气辉观测数据,结合地基独特的观测模式（天顶角为0° 的天顶方向和天顶角为45°的东西北南四个方向）对地基中高层大气风速进行反演,包括数据预处理、干涉环圆心确定、干涉环半径计算和风速反演. 将2010年5月6-13日8天十个环（十个干涉环同时参与反演）的反演结果与地基FPI风速实测数据进行比较,得到557.7nm,630.0nm,892.0nm三种谱线气辉的反演平均偏差分别为2.7m·s-1,5.5m·s-1,7.7m·s-1. 此外,基于反演算法对上述反演精度影响因素进行了分析. 研究发现,气辉辐射强度对风速的反演精度影响较大,气辉辐射越强,外环的半径计算精度越高,可参与的反演环数越多,则最终的风速反演精度越高. 而圆心偏差± 2pixel（五个环）和± 1pixel（十个环）及焦距变化（±10mm）对风速反演精度的影响相对较小,但当超出这一偏差范围,风速反演偏差会迅速增大.      

135.6nm夜气辉峰值电子密度反演算法及误差

根据夜间135.6nm大气辉光光强与F₂层峰值电子密度N_mF₂平方成正比的物理机制,在前期夜间135.6nm气辉辐射激发模型研究的基础上建立了峰值电子密度的反演算法,把全球经纬度分成若干格点,每个格点的电离层及中性成分信息分别由IRI2000和MSISE90提供,将电离层及中性成分廓线输入夜气辉辐射激发模型,计算每个格点135.6nm气辉的辐射强度,然后将各个格点的135.6nm气辉辐射强度与电离层廓线输入的N_mF₂平方拟合得到气辉强度与N_mF₂的转换因子.利用此方法可获得不同地方时、季节和太阳活动周期的转换因子组成查算表,进而根据实际探测的135.6nm气辉辐射强度反演相应时空的N_mF₂.最后对该算法的反演误差进行了综合分析,为该算法适用的时空特性提供重要理论支撑.      

氧气A(0,0)波段气辉体发射率和临边辐射强度模拟与分析

临近空间大气参数如温度、密度、风场等对预报模型精度及航天器运行安全等有较大的影响，而气辉的辐射模拟是大气参数反演的重要过程.本文基于光化学模型计算了氧气A（0，0）波段气辉的体发射率和临边辐射强度.基于氧气A（0，0）波段气辉的光化学反应机制、大气动力学和光化学反应理论，建立产生O₂（b1Σ_g+）的光化学模型.计算气辉体发射率，基于临边探测几何路径进行气辉辐射强度模拟.体发射率计算结果与AURIC模型结果的辐射值及辐射高度均一致.基于计算和模拟结果，对氧气A波段气辉体发射率和辐射强度的影响因素进行了分析.      

2000年和2001年52°N地区OI5577气辉强度与原子氧浓度峰值的时间变化特征

分析了2000年和2001年期间52°N地区OI5577气辉强度的夜间变化特征和季节变化特征．利用由 OI5577气辉强度反演原子氧浓度峰值的方法反演出原子氧浓度的峰值,分析了峰值的夜间变化特征和季节变化特征．结果表明, OI5577气辉强度的夜间变化特征随季节变化, 2000年春季的夜间强度最大值出现在0000LT 之后,夏季和秋季的出现在0000LT之前,冬季的出现在0000LT,2001年春季和秋季的夜间强度最大值出现在0000LT之前,夏季和冬季的出现在0000LT;OI5577气辉强度在2000年2月份,8月份和10月份出现最大值,在2001年9月份有最大值．就主要特征而言,反演出的原子氧浓度峰值的夜间变化特征和季节变化特征分别与OI5577气辉强度的一致．     

Adelaide地区大气重力波的气辉观测

利用澳大利亚Adelaide(34.5°S,138.5°E)地区7年(1995-2001年)的OH和OI气辉观测数据,以及同地区中频雷达所测背景风场数据,通过最大熵谱分析方法,统计分析了该地区大尺度重力波的传播特性.结果表明,(1)在中层顶气辉观测区,利用OH气辉探测到48个重力波事件,利用OI气辉探测到29个重力波事件,这些重力波的周期和水平相速度分别集中在68 min和36 m/s左右,具有东南向的优势传播方向,平均仰角为8°～10°,接近水平方向传播;(2)通过OH气辉和OI气辉观测到了同一个重力波事件,并根据两个高度上观测到的扰动相位差判断该重力波为上行波.      

基于最优估计法的瑞利激光雷达反演大气温度研究

基于瑞利激光雷达的回波光子信号对中层大气进行探测，结合最优估计法，对大气温度进行反演。本文基于瑞利散射激光雷达方程建立正向模型，选择大气模型的温度廓线作为先验状态信息，构建用于最优化处理的成本函数，利用Levenberg-Marquardt最优化算法对成本函数执行最优化处理，得到大气温度的反演结果，对反演结果的不确定度分析的同时利用平均核矩阵对反演结果中真实信息的贡献进行评估。利用瑞利激光雷达方程产生的模拟回波信号进行了大气温度的反演处理与分析，对中国科学院国家空间中心提供的瑞利激光雷达实测数据进行大气温度的最优估计反演。结果表明，90 km以下的反演不确定度在10 K以内，且相较于CH方法，最优估计法具有反演有效范围高的优势；在回波光子信噪比较高的区域，反演不确定度较小，且真实信息对反演结果的贡献占主导地位。     

利用卫星两行轨道根数反演热层密度

两行轨道根数（TLEs）是基于一般摄动理论产生的用于预报地球轨道飞行器位置和速度的一组轨道参数,通过求解大气阻力微分方程,可反演出热层大气密度. 本文选取近圆轨道CHAMP卫星和椭圆轨道Explorer8卫星,以两行轨道根数数据为基础,计算反弹道系数,并根据不同轨道特征采用两种不同反演方法对热层大气密度进行研究. 结果表明,这两种方法反演得到的大气密度与实测值均符合较好,其中CHAMP卫星的反演结果和经验模式值相对于实测值的误差分别为7.94%和13.94%,Explorer8卫星的误差分别为9.04%和14.32%. 相比模式值,利用两行轨道根数数据反演的热层大气密度更接近于实测值,说明该方法可以作为获取大量可靠大气密度数据的一种有效途径.      

2009年1月5日廊坊OH气辉观测图像的谱分析

2009年1月5日在中国河北省廊坊市韩村镇(39.4°N,116.6°E)进行了中国首次中间层顶大气重力波成像观测实验,记录了近4 h的OH气辉辐射数据,给出了依据该数据计算所得的该时间段内廊坊韩村附近水平方向约185 km范围内的中间层顶OH气辉扰动的谱分析结果.所得到的传播方向确定的二维功率谱和角度谱揭示了该时间段内重力波活动的波长和传播方向分布特点,表明波长下限较短,西向传播分量明显大于东向分量.     

夜间135.6 nm气辉反演的电离层f0F2与测高仪观测比较研究

在夜间电离层，气辉135.6 nm谱线主要由F层的O⁺和电子的辐射复合过程以及O⁺和O^–的中性复合过程激发，该谱线强度和电离层峰值电子密度Nm F₂存在很强的相关性。利用夜气辉135.6 nm辐射强度与F₂层峰值电子密度Nm F₂的平方成正比的物理模型，建立了在不同经纬度、地方时、季节和太阳活动下均适用的反演算法。通过DMSP卫星上搭载的紫外光谱成像仪(SSUSI)实际观测的135.6 nm气辉辐射强度来反演相应时空的电离层F₂层临界频率f₀F₂，并将其与地基测高仪探测结果做了综合对比。结果表明，在太阳活动高年(2013年)，相对误差小于等于20%的数据占比93.0%，平均相对误差约为7.08%；在太阳活动低年(2017年)，相对误差小于等于20%的数据占比80.8%，平均相对误差约为12.64%。最后，对该算法在太阳活动高低年的反演精度差异进行了分析。     

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.     

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.     

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.     

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。     

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).     

考虑误差不确定性的航空安全预测新方法

航空安全精确预测对预防事故意义重大。目前航空安全预测主要是确定性预测，忽略了各类不确定性对预测影响。在确定性预测基础上，考虑误差不确定性开展航空安全预测，通过非参数方法获得航空安全预测误差不确定性描述，基于最高密度域求解一定可靠程度航空安全预测值最可能落入区间，量化不确定性引起航空安全预测结果的变动，从而确定该区间包含航空安全预测值的可靠程度，更好地认识被预测量在未来变化中可能存在的不确定性和面临的风险。以某航空公司1994—2015年航空安全数据为例，采用所提方法对航空安全开展预测，结果表明，所提方法能提供航空安全预测值及其更精确的不确定性变化范围，更有利于从不确定性角度对航空安全进行分析，解释航空安全预测结果的可能性水平，能为航空安全预警和管理提供理论依据。      

The effect of surface reflection function and of atmospheric parameters on the shortwave radiation budget

Errors in the determination of the shortwave radiation budget from broadband satellite measurements at the top and at the bottom of a cloudless atmosphere due to uncertainties of the actual parameters of the atmosphere and the surface are derived by computer modelling. The model uses measured bidirectional reflectance functions and realistic values of the optical parameters of the atmosphere. Examples are presented which show the range of such uncertainties. Neglecting the anisotropy of the reflection function of land surfaces results in high uncertainties of the shortwave radiation budget, both at the top and the bottom of the atmosphere. The uncertainties caused by actual uncertain atmospheric parameters are low if data of the meteorological network are properly used.     

Uncertainties in estimates of the risks of late effects from space radiation.

Methods used to project risks in low-Earth orbit are of questionable merit for exploration missions because of the limited radiobiology data and knowledge of galactic cosmic ray (GCR) heavy ions, which causes estimates of the risk of late effects to be highly uncertain. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. Using the linear-additivity model for radiation risks, we use Monte-Carlo sampling from subjective uncertainty distributions in each factor to obtain an estimate of the overall uncertainty in risk projections. The resulting methodology is applied to several human space exploration mission scenarios including a deep space outpost and Mars missions of duration of 360, 660, and 1000 days. The major results are the quantification of the uncertainties in current risk estimates, the identification of factors that dominate risk projection uncertainties, and the development of a method to quantify candidate approaches to reduce uncertainties or mitigate risks. The large uncertainties in GCR risk projections lead to probability distributions of risk that mask any potential risk reduction using the "optimization" of shielding materials or configurations. In contrast, the design of shielding optimization approaches for solar particle events and trapped protons can be made at this time and promising technologies can be shown to have merit using our approach. The methods used also make it possible to express risk management objectives in terms of quantitative metrics, e.g., the number of days in space without exceeding a given risk level within well-defined confidence limits.     

ITRS/GCRS transformation: Uncertainty propagation analysis and short-term modelling of IAU 2006/2000A developments

A study of the uncertainty propagation in ITRS/GCRS transformation is presented in this work. General law of propagation of variances is applied to the ITRS/GCRS transformation matrix, deriving the analytical expressions to compute GCRS position uncertainty. This evaluation is based on EOP uncertainties provided by IERS long-term series and formal uncertainties of ITRS-compatible coordinates. Numerical results for the period 1998–2016 are shown and discussed for ITRS positions in different altitudes and latitudes, providing graphical and numerical insights of the mapping of EOP uncertainties to transformed coordinates.Eventually, an analysis of short-term evolution of the Celestial Intermediate Pole coordinates in the GCRS provided by the IAU2006/2000A precession-nutation model is carried out, in order to assess the feasibility to potentially broadcast these parameters in GNSS navigation message. This approach would facilitate the dissemination of terrestrial-celestial transformation parameters for real time users, given that polar motion and UT1-UTC are already foreseen in GPS interface specification. The results presented in this work confirm the feasibility of this idea.