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Thermospheric density and satellite drag modeling.

机译:热圈密度和卫星阻力建模。

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摘要

The United States depends heavily on its space infrastructure for a vast number of commercial and military applications. Space Situational Awareness (SSA) and Threat Assessment require maintaining accurate knowledge of the orbits of resident space objects (RSOs) and the associated uncertainties. Atmospheric drag is the largest source of uncertainty for low-perigee RSOs. The uncertainty stems from inaccurate modeling of neutral atmospheric mass density and inaccurate modeling of the interaction between the atmosphere and the RSO. In order to reduce the uncertainty in drag modeling, both atmospheric density and drag coefficient (CD) models need to be improved.;Early atmospheric density models were developed from orbital drag data or observations of a few early compact satellites. To simplify calculations, densities derived from orbit data used a fixed CD value of 2.2 measured in a laboratory using clean surfaces. Measurements from pressure gauges obtained in the early 1990s have confirmed the adsorption of atomic oxygen on satellite surfaces. The varying levels of adsorbed oxygen along with the constantly changing atmospheric conditions cause large variations in CD with altitude and along the orbit of the satellite. Therefore, the use of a fixed CD in early development has resulted in large biases in atmospheric density models.;A technique for generating corrections to empirical density models using precision orbit ephemerides (POE) as measurements in an optimal orbit determination process was recently developed. The process generates simultaneous corrections to the atmospheric density and ballistic coefficient (BC) by modeling the corrections as statistical exponentially decaying Gauss-Markov processes. The technique has been successfully implemented in generating density corrections using the CHAMP and GRACE satellites. This work examines the effectiveness, specifically the transfer of density models errors into BC estimates, of the technique using the CHAMP and GRACE satellites.;Moving toward accurate atmospheric models and absolute densities requires physics based models for CD. Closed-form solutions of CD have been developed and exist for a handful of simple geometries (flat plate, sphere, and cylinder). However, for complex geometries, the Direct Simulation Monte Carlo (DSMC) method is an important tool for developing CD models. DSMC is computationally intensive and real-time simulations for CD are not feasible. Therefore, parameterized models for CD are required.;Modeling CD for an RSO requires knowledge of the gas-surface interaction (GSI) that defines the manner in which the atmospheric particles exchange momentum and energy with the surface. The momentum and energy exchange is further influenced by likely adsorption of atomic oxygen that may partially or completely cover the surface. An important parameter that characterizes the GSI is the energy accommodation coefficient, &agr;.;An innovative and state-of-the-art technique of developing parameterized drag coefficient models is presented and validated using the GRACE satellite. The effect of gas-surface interactions on physical drag coefficients is examined. An attempt to reveal the nature of gas-surface interactions at altitudes above 500 km is made using the STELLA satellite.;A model that can accurately estimate CD has the potential to: (i) reduce the sources of uncertainty in the drag model, (ii) improve density estimates by resolving time-varying biases and moving toward absolute densities, and (iii) increase data sources for density estimation by allowing for the use of a wide range of RSOs as information sources. Results from this work have the potential to significantly improve the accuracy of conjunction analysis and SSA.
机译:美国在许多商业和军事应用中严重依赖其太空基础设施。空间态势感知(SSA)和威胁评估要求保持对常驻空间物体(RSO)的轨道及其相关不确定性的准确了解。大气阻力是近距RSO不确定性的最大来源。不确定性源于对中性大气质量密度的不正确建模以及对大气与RSO之间相互作用的不正确建模。为了减少阻力模型的不确定性,需要同时改善大气密度模型和阻力系数(CD)模型。早期的大气密度模型是根据轨道阻力数据或一些早期紧凑型卫星的观测结果开发的。为了简化计算,从轨道数据得出的密度使用在实验室中使用干净表面测量的固定CD值2.2。从1990年代初获得的压力表进行的测量已经证实,原子氧在卫星表面的吸附。吸附氧含量的变化以及不断变化的大气条件会导致CD随高度和卫星轨道的变化而变化很大。因此,在早期开发中使用固定CD会导致大气密度模型产生较大偏差。;最近开发了一种技术,用于在最佳轨道确定过程中使用精密轨道星历表(POE)作为测量值来对经验密度模型进行校正。该过程通过将校正建模为统计指数衰减的高斯-马尔可夫过程,从而同时对大气密度和弹道系数(BC)进行校正。使用CHAMP和GRACE卫星在生成密度校正中已成功实施该技术。这项工作检验了使用CHAMP和GRACE卫星的技术的有效性,特别是将密度模型误差转换为BC估计。向准确的大气模型和绝对密度过渡需要CD的基于物理的模型。已经开发了CD的闭式解决方案,并且存在一些简单的几何形状(平板,球体和圆柱体)。但是,对于复杂的几何图形,直接模拟蒙特卡洛(DSMC)方法是开发CD模型的重要工具。 DSMC是计算密集型的,并且CD的实时仿真是不可行的。因此,需要CD的参数化模型。RSO的CD建模需要了解气体表面相互作用(GSI),该相互作用定义了大气粒子与表面交换动量和能量的方式。动量和能量交换还受到可能部分或完全覆盖表面的原子氧可能吸附的影响。表征GSI的一个重要参数是能量调节系数,使用GRACE卫星介绍并验证了开发参数化阻力系数模型的创新和最新技术。考察了气体表面相互作用对物理阻力系数的影响。使用STELLA卫星试图揭示海拔500 km以上的气体表面相互作用的本质。;可以准确估算CD的模型具有以下潜力:(i)减少阻力模型中的不确定性源,( ii)通过解决随时间变化的偏差并朝绝对密度方向发展来提高密度估计,以及(iii)通过允许使用范围广泛的RSO作为信息源来增加用于密度估计的数据源。这项工作的结果可能会大大提高合取分析和SSA的准确性。

著录项

  • 作者

    Mehta, Piyush Mukesh.;

  • 作者单位

    University of Kansas.;

  • 授予单位 University of Kansas.;
  • 学科 Engineering Aerospace.;Atmospheric Sciences.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 193 p.
  • 总页数 193
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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