基于随机路径点模型的Ad hoc网络复杂统计特性

为了采用复杂网络理论指导Ad hoc网络拓扑结构特性研究,首先介绍复杂网络结构统计特性和随机路径点模型,并从理论上分析基于随机路径点模型的Ad hoc网络的度分布和聚类系数.利用仿真试验的方法产生基于随机路径点模型下的Ad hoc网络各种移动场景,得出Ad hoc网络在这些移动场景下的平均最短路径长度、聚类系数和度分布等复杂统计特性.通过分析仿真试验数据回答Ad hoc网络是否具有小世界效应、Ad hoc网络度分布形态如何以及是否具有无标度属性等问题.      

基于特性关联的产品工程更改传播

从特性关联入手分析并讨论更改传播,提出产品设计中特性关联单元的类型划分,论述特性关联单元的更改传播特征,进而归纳出更改传播的方式、更改传播展开过程以及特性在传播过程中的行为特性.所提出的工程更改传播过程模型为产品设计工程更改方案优化和传播风险评估提供了模型基础.通过气缸设计更改实例对提出的理论进行了初步验证.     

火星空间磁场结构特征

在火星空间模拟的单流体MHD模型的基础上, 研究了火星空间磁场结构及火星表面局部磁异常对磁场结构的影响. 在太阳风与火星相互作用的过程中, 形成弓激波和磁堆积区, 行星际磁场弯曲并向两极移动且被拖拽变形, 大部分磁力线从火星两极绕过, 通过火星之后在磁尾留下V字形结构. 火星表面附近局部磁异常也对火星磁场结构产生不可忽视的影响. 不同位置和强度的磁异常与太阳风相互作用形成结构及形态各异的微磁层, 如被拖拽的微磁层和存在开磁力线的微磁层等. 局部磁异常改变了近火磁场结构, 并可能改变等离子体的分布.      

函数调用网络的结构属性及其静态鲁棒性

通过对开源软件tar和MySQL源码的分析,构建基于函数调用的有向软件网络模型,研究函数调用网络的度分布、聚类系数等多个结构属性。结果表明,多个主要软件模块的耦合才使得整个函数调用网络具有高聚类特性;节点的依赖度(影响度)与节点的出度(入度)存在正相关性;节点的依赖度与影响度具有负相关性。基于有向软件网络鲁棒性的弱连通和强连通指标,采用不同节点攻击策略验证函数调用网络的静态鲁棒性。研究结果表明,对于tar网络,高出度策略对网络的弱连通性具有最佳的攻击效果;对于MySQL网络,高入度策略对网络的弱连通性具有最佳的攻击效果。      

温度扰动激发的重力波波包非线性传播过程的数值研究

采用谱配置方法建立了一个中层大气扰动传播的全非线性动力学数值模型，利用该模型对具有高期分布的波状温度扰动在可压大气中的演变和传播过程进行数值模拟，模拟结果表明：温度扰动很快就会激发出两支重力波波包，其中一支向上传播，而另一支则向下传播；这两支重力波波包的传播路径与线性理论给出的射线路径有些差异，进一步的数值分析则表明，给定的温度扰动在经过约3h的演变后，完全转化为波动，在这个转化过程中，79％的扰动能量转化为波动能量。     

航天器异常与空间环境

本文研究考查了靠近或在地球同步轨道上的ＳＣＡＴＨＡ、ＴＤＲＳ－１卫星以及ＧＰＳ、ＧＯＥＳ卫星组等的各自１０年左右运行时间中,空间环境所导致航天器异常的发生率的年分布特征,月分布特征,地方时分布特征以及不同类型的发生率分布特征。结果表明,由于不同空间环境因素对航天器作用不同,引起异常类型不一样,因此,太阳长周期和短月,地方时周期活动对航天器异常发生率影响无简单的统一规律特征;长周期中的单粒子事件是由     

重力波波包在可压大气中的非线性传播

本文采用二维全隐欧拉(FICE)格式对具有高斯分布的重力波波包在等温、可压大气中的非线性传播过程进行数值模拟和分析.数值分析结果表明:尽管存在非线性效应,在整个传播过程中,波动的等相面向下运动,波包和波相关能量向上传输.波相关扰动速度随高度增加指数增长,并且波与平流会发生非线性相互作用,最后导致平均流场增强.这与线性重力波理论完全一致.重力波波包的传播路径与重力波线性射线理论预言非常接近,但平均水平群速度和平均垂直群速度均明显小于线性射线理论给出的结果,可见波动的非线性过程会改变波相关能量的传输速度.模拟结果首次定量地展示出非线性效应对重力波波包传播的影响,表明建立在线性理论框架中的重力波运动学定义的合理性.      

波状扰动激发的重力波波包在中层大气中能量传播和转换特性的数值研究

采用谱配置方法对具有高斯分布的波状扰动激发重力波过程中的能量传播和转换特性进行数值研究．模拟结果表明：初始时刻单一的水平风、垂直风、密度或温度的波状扰动都可以激发出两支重力波波包，其中一文向上传播，而另一支则向下传播；在相同的波参数下，4种波状扰动所激发的重力波波包的能量传播路径几乎完全一致，与线性理论给出的射线路径却有些差异．进一步的数值分析则表明：4种波状扰动转化为波动的特征时间基本相等，约为2个波动周期，但是在这个转换过程中，不同扰动的能量转换效率却差别很大．     

一种基于生成对抗网络的卫星异常检测方法

针对卫星地面测控中心在异常检测时面临的遥测数据不平衡和缺乏异常标签等问题,提出了一种基于时序生成对抗网络的异常检测方法.首先对卫星遥测数据进行预处理,剔除原始数据中的噪声和野值.然后使用长短时记忆网络构建生成模型的生成器和判别器,使得模型可以学习到历史数据的时间依赖关系.采用改进的生成对抗损失函数,使得生成模型在训练时可以保证生成序列与输入序列的潜在空间分布一致.最后,使用残差作为测试序列的异常分数,通过阈值自适应方法判断测试序列是否异常.经真实卫星遥测数据进行实验验证,表明该异常检测方法具有较好的有效性.     

赤道异常峰区电离层的某些特点

由于赤道异常北峰覆盖我国整个南部地带,因此对峰区电离层特征的研究就成为掌握中国电离层特点的关键之一。本文试图对以下六个问题作些介绍和评述:1.逐日起伏和子夜前极大;2.峰位置的移动;3.赤道异常的经度效应;4.不均匀结构引起的强闪烁和快速法拉第衰落;5.顶部电离层的离化突起和中性赤道异常;6.粒子沉降的双峰分布.      

一种前馈神经网络的变误差主动式学习算法

研究误差反向传播多层前馈神经网络的主动式学习方法.文章分析了目前用于训练前馈神经网络改进BP算法的特点和存在的不足,在此基础上提出逐次主动调整网络学习误差的网络训练思想,根据网络输出误差趋势,主动变化输出层的调整误差δ_pl,使W\+k\-\{ji}和θ\+k\-j在调整过程中受到每次学习效果信息的控制,从而得到一种主动式变误差的学习算法.实验表明,在训练多层前馈神经网络时,变误差主动式算法的学习效率比改进BP算法的学习效率有明显提高.     

裂纹扩展寿命安全可靠性分析模型研究

通过分析影响裂纹扩展寿命的多个随机因素,就目前较为常用的裂纹扩展寿命安全可靠性分析模型进行比较.在此基础上,本文提出了一种新的模型--裂纹扩展寿命~断裂韧度可靠性分析模型,该模型基于目前比较公认的裂纹扩展寿命分布和断裂韧度分布特性,为工程界进行含裂纹结构的概率损伤容限评估提供一定的理论依据.     

瑞利索莫菲衍射与物理光学积分的应用比较

针对准光学中电磁场传播的计算问题,研究了从不同角度出发所采用的瑞利索莫菲标量衍射积分公式和基于矢量的物理光学积分公式内在的一致性与区别.首先从物理概念上区分这两种积分方法,然后在平行口面间电磁场传播的条件下,讨论两种积分公式的一致性.借助高斯波束传播解析解作对比,分别应用两种积分方法实现了高斯波束传播的数值仿真,给出了二者在处理电磁场传播问题时的精度与处理矢量衍射时的不同应用.     

Retrieval of spinach crop parameters by microwave remote sensing with back propagation artificial neural networks: A comparison of different transfer functions

Back propagation artificial natural network (BPANN) is a well known and widely used machine learning methodology in the field of remote sensing. In this paper an attempt is made to retrieve the spinach crop parameters like biomass, leaf area index, average plant height and soil moisture content by using the X-band scattering coefficients with BPANN at different growth stages of this crop. The maturity age of this crop was found to be 45 days from the date of sowing. After 45 days from the date of sowing, this crop was cut at a certain height for production. Then, it is a point of interest to investigate the microwave response of variation in production. Significant variations in all the crop parameters were observed after cutting the crop and consequently made the problem more critical. Our work confirms the utility of BPANN in handling such a non-linear data set. The BPANN is essentially a network of simple processing nodes arranged into different layers as input, hidden and the output. The input layer propagates components of a particular input vector after weighting these with synaptic weights to each node in the hidden layer. At each node, these weighted input vector components are added. Each hidden layer computes output corresponding to these weighted sum through a non-linear/linear function (e.g. LOGSIG, TANSIG and PURLIN). These functions are known as transfer functions. Thus, each of the hidden layer nodes compute output values, which become inputs to the nodes of the output layer. At nodes of output layer also a weighted sum of outputs of previous layer (hidden layer) are obtained and processed through a transfer function. Thus, the output layer nodes compute the network output for the particular input vector. In this paper, output nodes use linear transfer function. Different transfer functions e.g. TANSIG, LOGSIG and PURELIN were used and the performance of the ANN was optimized by changing the number of neurons in the hidden layers. The present analysis suggests the need of critical analysis of the BPANN in terms of selection of the best transfer function and other network parameters for the better results.     

Orbital error propagation considering atmospheric density uncertainty

Due to the influence of various errors, the orbital uncertainty propagation of artificial celestial objects while orbit prediction is required, especially in some applications such as conjunction analysis. In the orbital error propagation of artificial celestial objects in low Earth orbits (LEOs), atmospheric density uncertainty is one of the important factors that require special attention. In this paper, on the basis of considering the uncertainties of position and velocity, the atmospheric density uncertainty is also taken into account to further investigate the orbital error propagation of artificial celestial objects in LEOs. Artificial intelligence algorithms are introduced, the MC Dropout neural network and the heteroscedastic loss function are used to realize the correction of the empirical atmospheric density model, as well as to provide the quantification of model uncertainty and input uncertainty for the corrected atmospheric densities. It is shown that the neural network we built achieves good results in atmospheric density correction, and the uncertainty quantization obtained from the neural network is also reasonable. Moreover, using the Gaussian mixture model - unscented transform (GMM-UT) method, the atmospheric density uncertainty is taken into account in the orbital uncertainty propagation, by adding a sampled random term to the corrected atmospheric density when calculating atmospheric density. The feasibility of the GMM-UT method considering atmospheric density uncertainty is proved by the further comparison of abundant sampling points and GMM-UT results (with and without considering atmospheric density uncertainty).     

Physical and model interpretation of HF radio propagation on the St. Petersburg–Longyearbyen (Svalbard) path

HF radio wave observations have been carried out with an oblique ionospheric sounding (OIS) method on the radio path from St. Petersburg to Longyearbyen (Svalbard), and experimental ionograms were obtained for December 2001. These ionograms have been analysed to investigate the impact of the main ionospheric trough (MIT) and magnetic disturbances on the signals on this path. The observations during weakly disturbed (K_р = 2) magnetic conditions on 14–15 December 2001 were compared with predictions from ray-tracing through a numerical model of the ionosphere. The ray-tracing computer program synthesizes the OIS ionograms by means of the “shooting method”. This method calculates trajectories of HF radio waves for different values of elevation angle and transmission frequency. There was a variety of calculated trajectories, from which we choose those which reach the receiver, and the selected paths provide a synthesis of the oblique ionograms. To simulate HF radio wave propagation, we apply a three-dimensional distribution of the electron density calculated with the mathematical model of the high-latitude ionosphere developed in the Polar Geophysical Institute (PGI). These numerical simulations permit us to interpret specific peculiarities of the OIS data such as abnormal propagation modes, increased delays of signals, enhanced MOF (maximum observed frequency) values etc. New results of the study are summarised as follows. (1) An unusual feature of the propagation along the path is the change of propagation mechanism during substorms on entering a path midpoint (or 1-hop reflection point) to the MIT. (2) Even weak substorms, having the distinguished intensities, lead to the appearance of different types of irregularities observed by the CUTLASS radar and therefore to the different propagation modes and F2MOF values. (3) The PGI model of the ionosphere was first used for ray-tracing at high latitudes. The model results are basically in a good qualitative agreement with experimental observations. This model provides the satisfactory agreement between the calculated and experimental F2MOF values while not correctly representing the fine structure of the experimental OIS ionograms at night. An agreement between the calculated and experimental data is better for day and evening hours than at night.     

Study of long path VLF signal propagation characteristics as observed from Indian Antarctic station,Maitri

To examine the quality and propagation characteristics of the Very Low Frequency (VLF) radio waves in a very long propagation path, Indian Centre for Space Physics, Kolkata, participated in the 27th Indian scientific expedition to Antarctica during 2007–2008. One Stanford University made AWESOME VLF receiving system was installed at the Indian Antarctic station Maitri and about five weeks of data were recorded successfully from the Indian transmitter VTX and several other transmitting stations worldwide. The quality of the signal from the VTX transmitter was found to be very good, consistent and highly stable in day and night. The signal shows the evidences of the presence of the 24 h solar radiation in the Antarctic region during local summer. Here we report the both narrow band and broadband VLF observations from this site. The diurnal variations of VTX signal (18.2 kHz) are presented systematically for Antarctica path and also compared the same with the variations for a short propagation path (VTX-Kolkata). We compute the spatial distribution of the VTX signal along the VTX-Antarctica path using the most well-known LWPC model for an all-day and all-night propagation conditions. The calculated signal amplitudes corresponding to those conditions relatively corroborate the observations. We also present the attenuation rate of the dominant waveguide modes corresponding to those propagation conditions where the effects of the Antarctic polar ice on the attenuation of different propagating waveguide modes are visible.     

基于混合动态信念传播的多无人机协同定位算法

针对多无人机(UAVs)协同定位问题,提出一种基于混合动态信念传播的定位算法。在部分无人机GPS信号丢失的情况下,该算法可根据其他无人机的GPS观测,相邻无人机之间的相对距离观测,以及无人机加速度计的输出,对每个无人机的位置和速度状态进行分布式在线估计。首先用因子图模型描述多无人机的联合信念状态,接着给出一种混合动态信念传播推理算法计算图模型中的每个变量节点(对应于每个无人机)状态的边缘后验分布。推理过程仅包括每个无人机对自身局部信息的处理以及相邻无人机之间的信息交互,因此该算法可完全分布式实现。通过仿真实验以及与传统协同定位算法的比较,表明了本文算法的有效性。