火星大气模型参数对MSL气动特性的影响

火星大气与地球大气截然不同,飞行器在进入火星时气动特性不同于地球再入. 大气模型的差异主要表现为气体组份、密度和温度等物理参数. 针对火星进入器MSL在进入-下降-着陆过程中的高超声速进入段,利用三维并行程序求解耦合真实气体模型的流体动力学Navier-Stokes方程,分析MSL进入火星大气时大气模型参数对进入器气动特性的影响. 结果表明,通过与海盗号飞行数据的对比,验证了所采用的火星气体模型和计算方法,且其与NASA的 LAURA代码气动特性计算结果也较为一致;大气模型气体性质,即CO₂环境对进入器阻力系数和俯仰力矩系数影响较大,利用空气得到的计算和实验数据必须考虑CO₂效应;密度增大促进了化学非平衡效应,但对进入器气动特性基本没有影响;温度升高大大增强了化学非平衡效应,而对进入器气动特性影响较小.      

NRLMSISE-00大气模型与GRACE和CHAMP卫星大气密度数据的对比分析

利用GRACE(Gravity Recovery And Climate Experiment)和CHAMP(Challenging Mini-Satellite Payload)卫星2002-2008年的大气密度数据与NRLMSISE-00大气模型密度结果进行比较,分析了模型密度误差及其特点.结果显示,NRLMSISE-00大气模型计算的密度值普遍偏大,其相对误差随经纬度变化,在高纬度相对较小;相对误差随地方时变化,在02:00LT和15:00LT左右较大,10:00LT和20:00LT左右较小.通过模型密度相对误差与太阳F_10.7指数的对比分析发现,在太阳活动低年模型相对误差最大,而在太阳活动高年相对误差较小;将模型结果分别与GRACEA/B双星和CHAMP卫星的密度数据进行比较,发现对于轨道高度更高的GRACE卫星轨道,模型相对误差更大;在地磁平静期,相对误差与地磁ap指数(当前3h)相关性不强,但是在大磁暴发生时,误差急剧增大.      

地磁场模型简化计算方法

为了实现地磁导航在近地轨道卫星上的应用,需要解决传统的高斯球谐函数递推法在计算地磁场强度时存在方法复杂、计算量大、实时性难以保证等问题.针对上述问题,提出一种用地球磁场估计函数代替球谐函数的地磁场强度计算方法.该方法利用伪地心下的磁偶极子模型代替主磁场模型,通过多项式拟合离线得到高度范围内固定经纬度网格点的伪中心距系数,进而利用插值法和偶极子模型得到任意点的地磁场强度.仿真结果表明,轨道高度为300～500km,经纬度网格间隔为0.5°时,地球磁场估计函数法的导航精度与地球主磁场模型WMM精度一致的同时,降低了计算负担,提高了算法计算效率.      

低轨航天器弹道系数估算及热层大气模型误差分析

利用低轨（LEO）航天器在轨期间两行轨道根数（TLEs）数据,结合经验大气密度模型NRLMSISE00,反演计算得到其在轨期间的弹道系数B’,以31年B’的平均值代替弹道系数真值,分别通过标准球形目标卫星对比以及物理参数基本相同的非球形目标卫星对比,对弹道系数真值进行了检验;利用不同外形目标卫星弹道系数在不同太阳活动周内的变化规律,结合太阳和地磁活动变化,估计经验大气密度模型的误差分布. 结果表明,利用反演弹道系数31年的平均值来代替真值,其在理论值的正常误差范围内;大气密度模型误差在210～526km高度范围内存在相同的变化趋势,且模型误差随高度增加而增大;在短周期内B’变化与太阳活动指数F_10.7存在反相关性;密度模型不能有效模拟2008年出现的大气密度异常低. 以上结果表明,经验大气密度模型结果需要修正,尤其是在太阳活动峰年和谷年,此外,磁暴期间模型误差的修正对卫星定轨和轨道预报等也具有重要意义.      

升力式火星探测器进入轨迹优化设计仿真

针对升力式火星探测器在其完成星际转移轨道之后,由预定进入点开始反冲制动改变运行轨道进入火星大气,设计并仿真了进入段的轨迹优化。根据火星的大气密度及引力场参数,建立相应的火星大气模型及引力场模型,确定了升力式火星探测器的运动方程。在满足进入过程的约束条件下,采用遗传算法对进入轨道进行优化设计,提出不同的推力发动机制动方案并进行分析比较。结果表明,采用推力方案二能够实现性能指标最优,并求得着陆速度为136m/s,最终实现了探测器在火星表面的软着陆。     

基于阻力跟踪的火星大气进入段非线性预测制导律设计

针对火星探测任务大气进入段的高精度着陆问题,提出一种基于阻力跟踪的非线性预测制导策略。基于火星探测器大气进入段的三维运动模型,综合考虑探测器气动参数摄动、火星大气密度摄动、外部扰动以及进入时刻状态初值不确定性,设计了基于优化思想的非线性预测制导律,并对所提出的制导方法进行仿真验证。仿真结果表明:非线性预测制导律在满足控制约束的条件下可以获得较高的着陆精度。     

空间物体解体碎片云的长期演化建模与分析

空间碎片云由空间物体解体产生的大量空间碎片组成,由于其相对集中地分布在有限的空间内,将会对临近航天器产生较大的碰撞威胁。为了分析解体碎片云长期分布特点,文章首先利用数值积分方法对空间碎片云短期分布规律进行了研究;在此基础上,针对处于环状分布的碎片云,根据碎片所在的轨道高度和具有的面质比值,将碎片划分到不同分组,以每个组作为研究对象,建立了描述碎片云在大气阻力作用下的解析演化模型。模型避免了对单个解体碎片的运动状态进行积分,可大大降低对计算资源和计算时间的需求。考虑在高度为1422km 圆轨道上运行的物体,解体产生了1780个碎片,利用解析演化模型得到碎片云未来50年内的演化分布状态。数值结果表明,碎片云的峰值密度在解体物体轨道高度附近,并在大气阻力作用下向更大高度区间内扩散;较低高度区间内碎片密度具有先增加,然后在大气阻力作用下不断减少的特点。     

大气中子实时计算模式

为实时评估0~100km高度范围内的大气中子全球分布,对宇宙线在地磁场和大气中的传输过程进行了分析.利用蒙特卡罗方法工具包Geant4,预先计算不同能量的粒子在大气层中产生的次级粒子能谱分布,形成大气次级粒子数据库,并与相关模型进行对比,验证了该数据库的有效性和可靠性.以实测或预报的空间环境参数作为输入,计算同步轨道银河宇宙线和太阳质子事件能谱以及100km高度上的地磁垂直截止刚度,最终得到大气层顶上的粒子能谱.通过对大气次级粒子数据库的线性插值,实现1h分辨率的大气中子能谱和辐射剂量全球分布的实时计算.      

由电离层电位所建立的大气电状态

本文在已知电离层电位分布下, 解析地计算了大气电位, 电场和电流强度的全球分布.结果表明, 在大气导电率随高度呈指数增加的情况下, 100km高度上的电离层电位, 几乎无衰减地扫到25km以下.大气电场较强的区域主要在20km以下的低层大气区, 其垂直分量比水平分量大4个数量级.而中高层大气电场较弱, 且两分量量级相当.本文还提出了一种考虑地面形状对大气电场影响的解析方法.      

太赫兹火星大气临边探测仿真研究

对火星大气进行连续高分辨率观测是研究火星大气物理和化学过程的重要手段.太赫兹临边探测技术通过测量火星大气中的风和光化学循环中的重要气体（CO,O₃,H₂O,H₂O₂等）提高对火星的认知.针对火星大气遥感的探测需求,分析了300～1000GHz频段的频谱特征.针对探测卫星对于载荷质量、功耗等参数的要求,提出一个560GHz频段的火星大气太赫兹临边探测仪设计方案,并利用辐射传输模型ARTS中的行星工具箱进行仿真.仿真结果显示:火星大气温度的反演精度优于4K,其中45km高度以下优于2K;H₂O丰度的反演精度在90km以下优于50%,30km以下优于2%;H₂O₂的反演精度在40km以下优于50%;O₃的反演精度在50km以下优于60%;大气风速度的反演精度在65km以上优于5m·s-1,最高可以达到2m·s-1.研究结果表明,利用太赫兹波段的吸收谱线可以很好地探测火星大气中各成分的丰度、变化趋势以及中高层大气的风,可为后续火星表面及大气探测提供参考.      

大气密度变化对卫星返回轨道参数的影响

本文在考虑大气密度(90km高度以下) 随地理纬度、高度及时间(月份)随机变化的基础上,沿卫星的返回轨道建立了随机大气密度的统计模型。并应用该模型产生的随机大气密度样本,进行返回轨道的Monte Corlo法模拟计算。通过对模拟计算得到的返回轨道参数样本的统计处理,本文分析了大气密度变化对卫星返回轨道参数的影响。另外,本文还介绍了近似估计大气密度变化对返回轨道参数影响的影响系数法。     

精确星光大气折射导航观测模型的研究

高精度星光折射间接敏感地平的自主导航方法,目前被国内外广泛关注,由于大气参数变化的不确定性,国内外现用星光折射模型有一定局限性,使得利用星光折射导航定位精度大打折扣.根据大气密度随高度、纬度、季节等变化规律,有效改进现有固定高度(25km)的观测模型,可从整体上提高自主导航精度及可靠性.并通过对大气折射原理、平流层大气数据、大气模型以及影响星光折射观测模型的诸多因素的深入研究,建立了自适应连续高度(20~50km)的星光折射观测模型,同时建立带摄动的系统方程,利用Unscented卡尔曼滤波算法进行了计算机仿真研究,并对仿真结果进行了误差分析.      

Command generator tracker based direct model reference adaptive tracking guidance for Mars atmospheric entry

In order to accurately deliver an entry vehicle through the Martian atmosphere to the prescribed parachute deployment point, active Mars entry guidance is essential. This paper addresses the issue of Mars atmospheric entry guidance using the command generator tracker (CGT) based direct model reference adaptive control to reduce the adverse effect of the bounded uncertainties on atmospheric density and aerodynamic coefficients. Firstly, the nominal drag acceleration profile meeting a variety of constraints is planned off-line in the longitudinal plane as the reference model to track. Then, the CGT based direct model reference adaptive controller and the feed-forward compensator are designed to robustly track the aforementioned reference drag acceleration profile and to effectively reduce the downrange error. Afterwards, the heading alignment logic is adopted in the lateral plane to reduce the crossrange error. Finally, the validity of the guidance algorithm proposed in this paper is confirmed by Monte Carlo simulation analysis.     

类X-20高超声速飞行器反馈线性化控制研究

通过对类X-20高超声速飞行器的气动系数与高度、马赫数、攻角、侧滑角和舵偏角的关系进行分析,对各项气动系数进行了简化和拟合,并将舵偏增量视作控制输入,在此基础上建立了类X-20飞行器仿射非线性形式的控制模型,证明了它是可以输入输出精确线性化的,从而可以设计反馈线性化控制器.最后在存在大气密度、气动力矩系数和转动惯量不确定性情形下,针对原动力学模型进行闭环仿真研究,原动力学模型考虑地球旋转,气动数据直接从类X-20飞行器的气动数据表插值得到.仿真结果表明,所设计的控制律可以实现控制目标,具有较强鲁棒性.     

Global MGS TES data and Mars-GRAM validation

Mars Global Reference Atmospheric Model (Mars-GRAM 2001) is an engineering-level Mars atmosphere model widely used for many Mars mission applications. From 0 to 80 km, it is based on NASA Ames Mars General Circulation Model (MGCM), while above 80 km it is based on University of Michigan Mars Thermospheric General Circulation Model. Mars-GRAM 2001 and MGCM use surface topography from Mars Global Surveyor Mars Orbiter Laser Altimeter (MOLA). Validation studies are described comparing Mars-GRAM with a global summary data set of Mars Global Surveyor Thermal Emission Spectrometer (TES) data. TES averages and standard deviations were assembled from binned TES data which covered surface to ∼40 km, over more than a full Mars year (February 1999–June 2001, just before start of a Mars global dust storm). TES data were binned in 10° × 10° latitude–longitude bins (36 longitude bins, centered at 5°–355°, by 18 latitude bins, centered at −85° to +85°), and 12 seasonal bins (based on 30° increments of L_s angle). Bin averages and standard deviations were assembled at 23 data levels (temperature at 21 pressure levels, plus surface temperature and surface pressure). Two time-of-day bins were used: local time near 2 or 14 h. Two dust optical depth bins were used: infrared optical depth, either less than or greater than 0.25 (which corresponds to visible optical depth less than or greater than about 0.5). For interests in aerocapture and precision entry and landing, comparisons focused on atmospheric density. TES densities versus height were computed from TES temperature versus pressure, using assumptions of perfect gas law and hydrostatics. Mars-GRAM validation studies used density ratio (TES/Mars-GRAM) evaluated at data bin center points in space and time. Observed average TES/Mars-GRAM density ratios were generally 1 ± 0.05, except at high altitudes (15–30 km, depending on season) and high latitudes (>45°N), or at most altitudes in the southern hemisphere at L_s ∼ 90° and 180°. Compared to TES averages for a given latitude and season, TES data had average density standard deviation about the mean of ∼2.5% for all data, or ∼1–4%, depending on time of day and dust optical depth. Average standard deviation of TES/Mars-GRAM density ratio was 8.9% for local time 2 h and 7.1% for local time 14 h. Thus standard deviation of observed TES/Mars-GRAM density ratio, evaluated at matching positions and times, is about three times the standard deviation of TES data about the TES mean value at a given position and season.     

Tomographic reconstruction of the ionospheric electron density as a function of space and time

Electron density distribution is the major determining parameter of the ionosphere. Computerized Ionospheric Tomography (CIT) is a method to reconstruct ionospheric electron density image by computing Total Electron Content (TEC) values from the recorded Global Positioning Satellite System (GPS) signals. Due to the multi-scale variability of the ionosphere and inherent biases and errors in the computation of TEC, CIT constitutes an underdetermined ill-posed inverse problem. In this study, a novel Singular Value Decomposition (SVD) based CIT reconstruction technique is proposed for the imaging of electron density in both space (latitude, longitude, altitude) and time. The underlying model is obtained from International Reference Ionosphere (IRI) and the necessary measurements are obtained from earth based and satellite based GPS recordings. Based on the IRI-2007 model, a basis is formed by SVD for the required location and the time of interest. Selecting the first few basis vectors corresponding to the most significant singular values, the 3-D CIT is formulated as a weighted least squares estimation problem of the basis coefficients. By providing significant regularization to the tomographic inversion problem with limited projections, the proposed technique provides robust and reliable 3-D reconstructions of ionospheric electron density.     

Determination of land surface temperature using precipitable water based Split-Window and Artificial Neural Network in Turkey

Land surface temperature (LST) calculation utilizing satellite thermal images is very difficult due to the great temporal variance of atmospheric water vapor in the atmosphere which strongly affects the thermal radiance incoming to satellite sensors. In this study, Split-Window (SW) and Radial Basis Function (RBF) methods were utilized for prediction of LST using precipitable water for Turkey. Coll 94 Split-Window algorithm was modified using regional precipitable water values estimated from upper-air Radiosond observations for the years 1990–2007 and Local Split-Window (LSW) algorithms were generated for the study area. Using local algorithms and Advanced Very High Resolution Radiometer (AVHRR) data, monthly mean daily sum LST values were calculated. In RBF method latitude, longitude, altitude, surface emissivity, sun shine duration and precipitable water values were used as input variables of the structure. Correlation coefficients between estimated and measured LST values were obtained as 99.23% (for RBF) and 94.48% (for LSW) at 00:00 UTC and 92.77% (for RBF) and 89.98% (for LSW) at 12:00 UTC. These meaningful statistical results suggest that RBF and LSW methods could be used for LST calculation.