Investigations of the Krasnoyarsk Reservoir waters based on the multispectral satellite data

In this work historical investigations and modern results of classification of the Krasnoyarsk Reservoir are presented. The paper presents results of studying the dynamics of phytopigments and other optically active components, using multispectral satellite data. Several approaches to interpreting satellite data for optically complex inland water bodies are offered. Based on results of historical investigations it is shown that the spatial distribution of phytoplankton in the reservoir stems back to the time of its formation. Color index in the red spectral region (CIR) is introduced. A relationship between the color index and chlorophyll concentration is investigated. The CIR, derived from the AVHRR data, has been found to be related to chlorophyll concentration. Based on MODIS data, the waters of the Krasnoyarsk Reservoir have been classified in accordance with their optical spectral variability, using the technique of unsupervised IsoData classification. An empirical relationship between multispectral MODIS data and the ground-truth measurements of chlorophyll concentration has been found.     

Ozone destruction by solar electrons in relation to solar variability and the terrestrial latitude

Precipitating electrons from the radiation belts with energies greater than from 150 keV to 5 MeV have been correlated with ozone data of a large number of stations located within 40–70° N. Energetic electrons have been collected by the low altitude polar Russian satellite METEOR while ozone data have been compiled from almost ninety (90) stations located all over the world within the latitude zone 40–70° N.     

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.     

无人机遥感图像融合算法综述

遥感图像拼接融合技术可分为"像素级""特征级""决策级"3个级别;根据各级别特点,无人机遥感图像的融合应采用像素级的融合方法。文章对一些常见的像素级融合方法进行了简要描述,重点介绍了3种经典的图像融合方法,讲述了可以根据哪些指标对一幅图像从主观与客观两方面进行评价;在实验阶段,对3种经典融合方法进行了实验验证与性能分析。     

韦布尔背景下ODV检测器的筛选性能分析

研究了在韦布尔背景下一种基于ODV的恒虚警检测器。通过连续地使用基于ODV的统计量和相应的假设检验,这种检测器对有序样本进行删除来估计背景的噪声功率水平。在均匀背景及加入干扰两种情况下,通过仿真验证ODV方法的筛选性能。结果表明,ODV方法在韦布尔背景下的筛选性能是理想的,而且此方法不需要知道任何关于背景的先验信息,且具有自适应筛选的优点。     

我国股指期货套期保值策略及最佳套期保值率研究

套期保值是股指期货最主要的功能之一,针对我国股市的特点,首先研究在我国证券市场如何应用股指期货进行套期保值,在此基础上,采用两种不同的思路,给出确定最佳套期保值率的方法,并在初步的理论研究基础上,指出应用最小二乘法确定最佳套期保值率是一种合适的选择。该研究对我国股指期货的到来提供了先行理论,有一定的实际意义。     

基于多自由度飞机模型的机场道面平整度评价方法

从三自由度飞机模型出发,提出了新的机场道面平整度评价理论,以不同平整度等级的3条测线的道面高程作为输入,在Matlab/Simulink环境中对飞机的三自由度振动方程进行求解,得到飞机机身的3个振动响应量:纵向俯仰角φ、横向滚转角θ及质心处竖向位移。在此基础上计算出道面整机平整度指数(Full aircraft roughness index,FARI)沿跑道纵向的分布曲线;同时计算出相同道面的国际平整度指数(International roughness index,IRI)。分别将FARI,IRI与在相应道面上滑行的飞机加权加速度均方根值进行了相关性分析,相关系数分别为0.980 6和0.886 9。结果表明整机平整度指数FARI更能够客观反应飞机所有机轮覆盖范围内道面起伏情况对飞机滑行过程中颠簸量的影响效果,更适合于机场道面平整度的评价。     

氢气和过氧化氢对正癸烷燃烧特性影响的对比

氢气(H2)和过氧化氢(H2O2)具有较强的反应活性,能够增强碳氢燃料的燃烧过程。为了探究添加液态氢和液态过氧化氢对航空燃油燃烧特性的影响,以正癸烷为代理燃料,采用数值模拟方法对比研究了H2和H2O2对正癸烷/空气燃烧特性的影响。研究发现,随着H2O2的增加,点火延迟时间显著缩短;而随着H2的增加,初始温度为1100 K时,点火延迟时间基本不变,在初始温度为1600 K时点火延迟时间略有缩短。随着H2O2的增加,层流火焰速度有所提升,而H2添加量对层流火焰速度的提高相对而言较小。富油燃烧时,CO排放指数随H2O2和H2的增加有所降低,NO排放指数有所增长。低压贫油燃烧时,H2O2和H2添加量对CO和NO排放指数基本没有影响;高压贫油燃烧时CO排放指数有所降低,NO排放指数有所提高,H2O2添加量的影响更加显著。