空空作战飞机敏感性分析研究

为分析战斗机作战能力的敏感性，通过建立战斗机作战能力的指标体系，综合使用幂指数法和模糊参 差分析法对战斗机作战能力进行评估。采用基于方差的全局敏感性分析方法sobol 指数法分析战斗机作战能力 的敏感性，得到选取的输入变量的重要度排序和变量间的交互效应，将结果与熵值法结果进行对比，比较分析 sobol 指数法作敏感性分析的优势。     

基于综合指标的最优冗余陀螺配置确定方法

陀螺是航天器控制系统中的关键姿态敏感器,其主要采取冗余措施进行配置。针对航天器控制系统设计中如何进行陀螺冗余配置的问题,提出了一种确定最优冗余陀螺配置的方法,该方法综合考虑了系统的可靠性、精度、成本代价等综合指标。首先,以工程中普遍采用的陀螺斜置式为对象,系统性给出了陀螺斜置式的安装结构,并以测量误差最小为目标确定出确定安装数目下的最优陀螺冗余安装结构。其次,结合实际工程经验对陀螺冗余配置的综合性能指标进行详细系统的分析。然后,利用优化评价方法以综合指标为基础对不同安装数目下的陀螺冗余安装结构进行综合评价,确定出陀螺冗余配置的最优安装数目,即最优冗余陀螺配置。最后,利用该方法对实际工程中的斜置式陀螺冗余配置进行分析和计算。结果表明,当陀螺的安装数目为7时为最优冗余配置,该结论对实际工程具有理论指导作用。     

飞机燃油箱惰化中氧体积分数控制指标分析

对油箱惰化的氧体积分数控制指标,即极限氧体积分数,测定标准、理论与实验研究成果进行了较为系统地梳理与总结,并基于前人研究成果提出:①采用N2惰化时,对于RP-3燃油,其地面状态下,可采用12%作为油箱氧体积分数控制指标。②对于民机,飞行包线内燃油箱氧体积分数控制指标可为从海平面到3 048 m高度,油箱内气相空间极限氧体积分数不超过12%,3 048～12 192 m高度,不超过从12%线性增加到145%;对于军机,可以考虑在民机标准上增加20%安全裕度,即从地面的9%线性增加至12 192 m的12%。③目前国内军机惰化系统研制中,规定在整个飞行包线内控制燃油箱气相空间氧体积分数不超过9%的要求值得商榷,它将直接带来因过度防护而产生的代偿损失过大等问题。     

S形进气道流路造型方法及其对性能影响的研究

根据S形进气道的几何边界条件,提出了一种基于多项式的中心线及面积分布率曲线的流路造型方法。选择不同的拐点位置,采用该方法构造了9条具有代表性的中心线及面积分布率方程。组合不同的中心线和面积分布率曲线建立了相应的S形进气道的几何造型,并采用三维N-S方程进行求解,得到了总压恢复系数和DC60等性能指标。分析计算结果表明,中心线对S形进气道总压恢复和出口动压起着主要影响,随着中心线方程拐点位置后移,S形进气道总压恢复系数和出口动压呈明显增加趋势;中心线和面积分布率组合共同影响着DC60指标,当中心线拐点过于靠近进气道进口而面积分布率曲线拐点靠近进气道出口时,进气道下游的涡将会发展到出口,从而大幅度影响DC60指标。     

军用运输机运输效能指标

给出了运输任务类型和运输效能定义,从效果与耗费两方面着手建立了运输效能指标体系,将运输效能归纳为安全性、质量或体积、距离、准确性、时间、场地、人员、设备及费用等9种因素,在确立各个因素运输效能单项指标的基础上提出了一种运输效能综合指标,以四种典型运输任务为例,建立了常用的运输效能指标。     

Rainfall retrieval over Indian land and oceanic regions from SSM/I microwave data

Present study focuses on the estimation of rainfall over Indian land and oceanic regions from the Special Sensor Microwave/Imager (SSM/I) on the Defense Meteorological Satellite Program (DMSP) F-13. Based on the measurements at 19.35, 22.235 and 85.5 GHz channels of SSM/I Satellite, scattering index (SI) has been developed for the Indian land and oceanic regions separately. These scattering indices were co-located against rainfall from Precipitation Radar (PR) onboard Tropical Rainfall Measuring Mission (TRMM) to develop a new regional relationship between the SI and the rain rate for the Indian land and oceanic regions. A non-linear fit between the rain rate and the SI is established for rain measurement. In order to have confidence in our method, we have also estimated rainfall using the global rainfall and scattering index relationship developed by Ferraro and Marks [Ferraro, R.R., Marks, G.F. The development of SSM/I rain rate retrieval algorithms using ground based radar measurements. J. Atmos. Ocean. Technol. 12, 755–770, 1995]. The validation with the rain-gauge shows that the present scheme is able to retrieve rainfall with better accuracy than that of Ferraro and Marks (1995). Further intercomparison with TRMM-2A12 and validation with rain-gauges rainfall showed that the present algorithm is able to retrieve the rainfall with reasonably good accuracy.     

Surface temperature estimation in Singhbhum Shear Zone of India using Landsat-7 ETM+ thermal infrared data

Land surface temperature (LST) is an important factor in global change studies, heat balance and as control for climate change. A comparative study of LST over parts of the Singhbhum Shear Zone in India was undertaken using various emissivity and temperature retrieval algorithms applied on visible and near infrared (VNIR), and thermal infrared (TIR) bands of high resolution Landsat-7 ETM+ imagery. LST results obtained from satellite data of October 26, 2001 and November 2, 2001 through various algorithms were validated with ground measurements collected during satellite overpass. In addition, LST products of MODIS and ASTER were compared with Landsat-7 ETM+ and ground truth data to explore the possibility of using multi-sensor approach in LST monitoring. An image-based dark object subtraction (DOS3) algorithm, which is yet to be tested for LST retrieval, was applied on VNIR bands to obtain atmospheric corrected surface reflectance images. Normalized difference vegetation index (NDVI) was estimated from VNIR reflectance image. Various surface emissivity retrieval algorithms based on NDVI and vegetation proportion were applied to ascertain emissivities of the various land cover categories in the study area in the spectral range of 10.4–12.5 μm. A minimum emissivity value of about 0.95 was observed over the reflective rock body with a maximum of about 0.99 over dense forest. A strong correlation was established between Landsat ETM+ reflectance band 3 and emissivity. Single channel based algorithms were adopted for surface radiance and brightness temperature. Finally, emissivity correction was applied on ‘brightness temperature’ to obtain LST. Estimated LST values obtained from various algorithms were compared with field ground measurements for different land cover categories. LST values obtained after using Valor’s emissivity and single channel equations were best correlated with ground truth temperature. Minimum LST is observed over dense forest as about 26 °C and maximum LST is observed over rock body of about 38 °C. The estimated LST showed that rock bodies, bare soils and built-up areas exhibit higher surface temperatures, while water bodies, agricultural croplands and dense vegetations have lower surface temperatures during the daytime. The accuracy of the estimated LST was within ±2 °C. LST comparison of ASTER and MODIS with Landsat has a maximum difference of 2 °C. Strong correlation was found between LST and spectral radiance of band 6 of Landsat-7 ETM+. Result corroborates the fact that surface temperatures over land use/land cover types are greatly influenced by the amount of vegetation present.     

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.     

S型进气道沿程结冰参数变化的数值模拟

采用欧拉-欧拉法,对低来流马赫数和大气结冰条件下S型进气道沿程的空气-过冷水滴两相流场进行了数值计算,获得了进气道沿程和出口面上结冰参数的分布和变化特征.计算结果表明:当来流马赫数从0.1增加到0.5时,进气道入口处附近相对于来流的气动降温从6K增大到17K左右,进气道出口面上的温度畸变指数逐渐增大,液态水含量畸变指数先急剧增大后缓慢减小,在研究范围内来流马赫数为0.2时液态水含量畸变值达到最大.      

基于核部分非负矩阵分解的亚像元级地物光谱分析

为了进一步提高亚像元级地物的光谱分析精度,提出了一种基于核部分非负矩阵分解(Kernel Protection Non-negative Matrix Factorization,KPNMF)的非线性解混算法.首先通过基于凸面几何理论的端元提取方法提取纯像元端元候选像素集合,然后根据候选像素的空间纯度指数判断纯像元端元.在纯像元端元信息已知的条件下,利用核方法对部分非负矩阵分解(Protection Non-negative Matrix Factorization,PNMF)进行推广,构造相应的目标函数,推导迭代求解过程,分解求得亚像元端元光谱和所有端元的丰度.试验结果表明,提出的解混算法具有良好的非线性分解能力,解混结果优于线性解混算法.