一种区域参考大气密度的建模与应用方法

为满足空天试验研究中对参考大气模型的实际需求,即模型应具有跨时空的全球尺度覆盖性以及在起降关键航迹点的高精度性,提出了一种区域参考大气密度的建模与应用方法。首先对实测数据的冬夏季典型月份的大气密度特性,具体包括月均值与密度扰动进行统计分析,在此基础上提出了基于探空试验实测数据的全球参考大气模型（GRAM）的定量修正方法,从而构建起了包含有大气扰动与季节变化的区域参考大气密度模型。最后提出了区域参考大气密度模型向GRAM的过渡方法与实际应用方法。研究表明,探测地区的大气密度特性具有明显的冬夏季节性差异,需要根据季节构建相应的大气密度模型。区域参考大气模型的蒙特卡罗仿真可以有效模拟实测数据的大气密度特性。通过与GRAM过渡结合,参考大气模型既具有全球覆盖性,又具有很高的局部精度。      

临近空间大气化学过程快速建模技术初探

围绕临近空间大气化学过程数值模拟计算问题,以平流层大气4个典型光化学系统为例,运用化学动理学预处理（KPP）工具,对不同复杂度的光化学反应质量平衡方程体系进行预处理,快速建立各系统化学动理学方程组的代数表示;针对模型中的大刚性ODE方程组,选取6种不同的数值计算方案（rodas,ros3,ros4,rosenbrock,sdirk,seulex） , 实现ODE方程组的离散表示,并自动生成所需计算代码。在此基础上,开展平流层光化学过程数值模拟试验,重点考察了：各数值计算方案的计算效率和计算稳定性;各系统主要化学成分随着时间的演化规律;光化学系统复杂度对各模型主要成分变化的影响。模拟结果显示：KPP工具能有效应对临近空间大气化学反应系统复杂度的增长,缩短大气化学模型建模与检验周期,为临近空间大气化学过程研究提供有效技术支撑。

     

临近空间大气密度扰动对高超声速飞行器气动热环境的影响

基于TIMED/SABER 2002—2018年大气密度观测数据,统计分析了20~80 km大气密度扰动对高超声速飞行器飞行热环境的影响。根据驻点热流估算方法给出的大气密度变化量与热流变化量之间的关系,定性和定量分析了不同月份大气密度相对变化量引起的热流变化量在垂直和水平方向的分布特征。研究表明:SABER大气密度月年均值计算的热流相对USSA76在夏季半球中高纬度地区偏高,在冬季半球偏低。在夏季半球高纬度地区约80 km附近存在热流增量的极大值,南半球夏季的极大值高于北半球夏季,尤其在南半球1月份,热流偏高可达32.2%。在经度方向,热流分布在夏季半球差异较小,冬季半球差异较大;考虑真实大气中存在的扰动时,在南半球和北半球夏季80 km附近,SABER大气密度预测的热流分别比USSA76偏高可达40.7%和36.6%。在经度方向,大气扰动引起的热流经向分布差异显著。在飞行器设计时,大气扰动的影响不能忽略;高超声速飞行器飞行应避免在夏季穿越南半球和北半球,规避热流增加带来的风险。      

时间序列法在临近空间大气风场预报中的应用

受多种因素影响,临近空间大气环境要素复杂多变,预报难度很大.本文采用时间序列法中的自回归滑动平均（ARMA）模型对临近空间大气风场开展统计预报方法研究,基于廊坊（39.4°N,116.7°W）中频雷达在88km高度的大气纬向风数据开展预报试验.本次预报试验的样本数据为2015年9月24日至10月24日风场数据,利用过去7天数据对未来第8天风场数据进行预报.试验结果显示,ARMA模型对临近空间大气风场预报有一定的适用性.当风场变化规律性较强,即样本数据风场呈现出比较显著的24h周期性变化时,ARMA模型预报效果较好;当风场发生突变时,预报效果变差.与实测数据的对比结果表明,ARMA模型预报结果的误差在9~27m·s^-1,预报效果优于同阶自回归（AR）模型,略优于高阶AR模型.     

太阳活动突发过程对临近空间大气影响的模拟

空间天气对地球及近地空间具有重要影响,大的空间天气事件对中上层大气动力学和成分具有不同的影响。利用全大气耦合模式WACCM,针对太阳耀斑、太阳质子、地磁暴三类事件,以太阳活动平静期2015年5月10-14日的GEOS-5数据为模式背景场,通过F_10.7、离子产生率、Kp及Ap指数设置,分别模拟三类事件对临近空间大气温度、密度和臭氧的影响。结果表明耀斑事件在三类事件中对临近空间大气温度和密度的影响最为显著。平流层大气温度增加是由耀斑辐射增强引起平流层臭氧吸收紫外辐射发生的光化学反应所致,耀斑事件引起平流层和低热层温度增加约为2～3 K,低热层大气相对密度增加在6%以内;太阳质子事件及磁暴事件主要影响低热层,但太阳质子事件和磁暴事件对低热层温度扰动不大于1 K。     

一种火星大气密度三维解析模型

根据火星大气数据库,建立了以高度和经纬度为输入的火星三维解析大气密度模型;在竖直方向上,采用分层指数模型;在水平方向上,将指数模型中的参考密度和参考高度视为经纬度的多项式函数,并通过最小二乘曲面拟合得到了多项式系数。相比传统的指数模型,三维指数模型不仅反映了火星大气密度随高度的变化规律,而且能够体现出大气密度在水平方向上的变化。与大气数据库相比,三维密度模型具有解析形式,计算速度快,仿真过程中只需存储简单的多项式系数即可实现密度的实时计算和调用,适用于地面实时仿真。     

临近空间大气环境落球探测中的科氏力影响

气象火箭落球探测技术是临近空间大气环境探测的重要方法。在落球探测数据处理过程中,通常忽略科氏力项的影响。本文利用经验预报模式构建落球探测正演仿真模型,并根据落球探测原理建立参数反演模型,在此基础上仿真模拟了落球探测数据处理过程中忽略科氏力项对大气参数反演精度的影响。在95~100 km高度范围内,忽略科氏力项将引起温度、密度、纬向风和经向风等大气参数较大反演误差,其误差特性随探测点纬度、各方向初始速度等呈现不同的变化规律,之后反演误差将随高度下降而逐渐下降。当高度下降至约70 km时科氏力项带来的影响基本可以忽略不计。研究结果表明在临近空间大气环境落球探测数据处理过程中不能忽略科氏力项的影响。本文结果对提高落球探测大气参数反演精度具有重要的参考价值。

     

临近空间飞行器

在ORS发展中,美军首次将临近空间飞行器与战术星、及时响应运载器统一纳入一个军事航天大系统中,提出由战术星、临近空间飞行器和及时响应运载器共同组成"联合作战空间"。超高空长航时无     

基于氧气A波段临近空间大气温度反演的贝叶斯与最小二乘法对比

基于氧气A波段的临边辐射模拟数据进行临近空间大气温度廓线的反演,分析比较了贝叶斯和最小二乘两种不同反演算法的特点.80km以下,信噪比为66～337时：基于贝叶斯理论反演的三条谱线761.59,762.2,764.05nm的反演误差平均值分别为5.52,3.94,4.73K;采用最小二乘法的反演误差平均值分别为10.57,7.04,8.80K.信噪比为6～34时：基于贝叶斯理论反演的三条谱线的反演误差平均值分别为18.27,12.18,18.27K;采用最小二乘法的反演误差平均值分别为103.18,68.79,85.98K.研究结果表明,基于贝叶斯理论的反演方法,利用先验信息对反演结果进行约束和修正,在有噪声的情况下获得了更合理的解,从而提高了反演精度和抗干扰能力.这为星载探测临近空间大气温度的算法研究和开发提供了参考,也为提高光谱仪器信噪比并进而提高温度反演精度提供了理论基础.     

Storm-time atmospheric density modeling using neural networks and its application in orbit propagation

Upper atmospheric densities during geomagnetic storms are usually poorly estimated due to a lack of clear understanding of coupling mechanisms between the thermosphere and magnetosphere. Consequently, the orbit determination and propagation for low-Earth-orbit objects during geomagnetic storms have large uncertainties. Artificial neural networks are often used to identify nonlinear systems in the absence of rigorous theory. In the present study, an attempt has been made to model the storm-time atmospheric density using neural networks. Considering the debate over the representative of geomagnetic storm effect, i.e. the geomagnetic indices ap and Dst, three neural network models (NNM) are developed with ap, Dst and a combination of ap and Dst respectively. The density data used for training the NNMs are derived from the measurements of the satellites CHAMP and GRACE. The NNMs are evaluated by looking at: (a) the mean residuals and the standard deviations with respect to the density data that are not used in training process, and (b) the accuracy of reconstructing the orbits of selected objects during storms employing each model. This empirical modeling technique and the comparisons with the models NRLMSIS-00 and Jacchia-Bowman 2008 reveal (1) the capability of neural networks to model the relationship between solar and geomagnetic activities, and density variations; and (2) the merits and demerits of ap and Dst when it comes to characterizing density variations during storms.     

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.     

Towards accurate atmospheric mass density determination Using precise positional information of space objects

This paper presents a new method of deriving atmospheric mass densities with a high temporal resolution from precise orbit data of low earth orbiting (LEO) space objects. This method is based on the drag perturbation equation of the semi-major axis of the orbit of LEO space objects which relates the change rate of the semi-major axis to the atmospheric mass density. The effectiveness of the new method is evaluated using the GFZ-ISDC GPS rapid science orbit (RSO) products of the CHAMP satellite over a time period of 3 months. The densities derived using this new method and obtained from accelerometer data are compared and good agreements are achieved. An example of using the derived density to generate good orbit prediction for CHAMP is presented.     

冲突证据决策新方法及应用

冲突证据决策方法研究是证据理论重要研究课题。鉴于现有的证据理论改进方法在冲突证据决策过程中存在计算量较大,归一化过程不合理,证据组合效果不理想等一系列问题,提出基于二次组合的冲突证据决策方法。首先,提出新的基于二次组合的冲突证据决策方法的流程图;然后,提出新的乘性归一化规则,并对新的乘性归一化规则进行算例分析,验证其合理性;最后,分析现有冲突度量函数的不足,并提出新的冲突度量函数,并分析冲突度量函数的合理性。通过算例分析,并与现有证据组合规则的比较表明,所提方法不仅计算量得以改善,组合结果也得到提升。      

空间电子设备辐射屏蔽方法的研究与软件实现

研究了空间电子设备辐射屏蔽分析的方法,利用计算机辅助设计(CAD)技术和软件开发工具,将复杂繁琐的计算过程编写成流程化的程序;利用三维CAD技术的二次开发功能,从Candence软件生成的记录文件中提取出信息,在计算机图形环境中高效自动地生成电路板模型;借助计算机交互技术,实现剂量点坐标的自动提取和保存;利用办公软件个性化设置功能,设计出提取背景信息的接口,实现了最终报告文档的自动生成.开发出的软件最终成功地实现了在不同结构和布局的空间电子设备中,在不同方向和位置上累积的空间带电粒子剂量值的计算,为电子设备结构的抗辐射设计提供了参考和依据.     

A global survey of COSMIC ionospheric peak electron density and its height: A comparison with ground-based ionosonde measurements

With a network of ground-based ionosondes distributed around the world, the ionospheric peak electron density and its height measured by FORMOSAT-3/COSMIC satellites in terms of GPS radio occultation technique are extensively examined in this article. It is found that, in spite of the latitude, the mean values of the peak electron density measured by COSMIC satellites are systematically smaller than those observed by ground-based ionosondes. The discrepancy between them is dependent on the latitude, namely, it is small in low and mid-latitudes and large in high-latitude region. Moreover, statistical analysis shows that the slopes of the regression line that is best fitted to the scatter diagram of occultation-retrieved peak electron density (ordinate axis) versus ionosonde-observed peak density (abscissa axis) are universally less than one. This feature is believed to be the result of path average effect of non-uniform distribution of the electron density along the GSP ray during the occultation. A comparison between COSMIC-measured peak height and ionosonde-derived peak height hmF2 indicates that the former is systematically higher than the latter. The difference in the two can be as large as 20% or more in equatorial and low-latitude regions. This result implies that the peak height hmF2 derived from the virtual height through true height analysis based on Titheridge method seems to underestimate the true peak height. The correlation between COSMIC and ionosonde peak electron densities is analyzed and the result reveals that correlation coefficient seems to be dependent on the fluctuation of the occultation-retrieved electron density profile. The correlation will be higher (lower) for the electron density profiles with smaller (larger) fluctuations. This feature suggests that the inhomogeneous distribution of the electron density along the GPS ray path during the occultation plays an important role affecting the correlation between COSMIC and ionosonde measurements.