中国及邻近地区地磁场垂直梯度的计算与研究

根据地磁场的球谐模型,推导出地磁场各个分量垂直梯度的球谐表达式.计算出中国及邻近地区高度为0km,50km和100km处的地磁场及其垂直梯度的网点值,编绘出地磁总强度、垂直强度、水平强度和磁偏角的垂直梯度等值线图.研究了地磁场垂直梯度在地面上以及随高度的变化规律.     

一种基于主星的导航星座构造方法

提出了一种基于主星的导航星座构造方法,利用不等式约束下多变量函数最优化问题的求解方法实现了导航主星的选取和导航星座的构造。实验表明,采用该方法构造的导航星座数据库,既不会造成导航星的丢失,又显著地减少了需要存储的识别基元的数量,从而有效地降低了导航星座数据库的存储容量。     

车辆导航系统中超前滞后校正方法

分析了车辆导航系统中超前滞后产生的原因,提出了利用地图匹配MM(Map Matching)进行GPS(Global Positioning System)/DRS(Dead Reckoning System)组合导航系统超前滞后校正的方法.该方法是将超前滞后误差归结为GPS误差,先利用GPS沿道路垂直方向上误差的可观测性进行GPS误差校正,再将校正的GPS信息与DRS信息进行卡尔曼滤波,从而减少组合导航系统超前滞后误差.仿真结果表明上述方法是行之有效的.      

Flood susceptibility mapping by ensemble evidential belief function and binomial logistic regression model on river basin of eastern India

Flooding is the overflow of water from stream, river, lake and sea that occurs all over the world and has disastrous effects on human society and environment. Frequent severe flood event in eastern India cause of death and damages every year so, the development of flood susceptibility method is needed for identifying the flood vulnerability areas to reduce the damages. Techniques of Remote Sensing (RS) and Geographical Information System (GIS) can help to flood susceptibility modeling by the accrued and analyzing huge amount of data in short time. The main objectives of this study are to determine the effectiveness of Evidence Belief Function (EBF), binomial Logistic Regression (LR) and ensemble of EBF and LR (EBF-LR) model with RS and GIS techniques for flood susceptibility mapping and spatial prediction of flood-susceptible areas in the Koiya river basin of West Bengal, India. Eight flood conditioning factors; Land use and land cover (LULC), soil, rainfall, normalized differences vegetation index (NDVI), distance to river, elevation, topographic wetness index (TWI) and stream power index (SPI) have been used, and total 264 historical flooding points were mapped, and randomly divided in to training (70%) and validating (30%) dataset. Flood susceptibility map has been generated by applying EBF, LR and ensemble EBF-LR method with the help of training and eight causative factors dataset. The maps have been divided in to six classes; extremely low, very low, low, moderate, high and very high. The receiver operating characteristic (ROC) curve has been used to accuracy assessment of the susceptibility map, and the area under curve (AUC) disclosures 87.9%, 85.2% and 84.1% prediction rate for the EBF-LR, EBF and LR model, respectively. This study is helpful to flood management program, dissection makers and planning in local administrative level.     

基于加权朴素贝叶斯分类器和极端随机树的蛋白质接触图预测

提出一个新的基于集成学习的预测器(TargetPCM),对蛋白质接触图(特别是中长程)进行高精度的预测。首先,TargetPCM使用加权朴素贝叶斯分类器(Weighted Nave Bayes classifier,WNBC)融合3个接触图预测器的输出,其中WNBC中的权重参数通过粒子群算法优化得到;其次,将WNBC融合后的输出和基于序列的特征进行组合,得到更具鉴别能力的特征;在此基础上,应用极端随机树训练得到最终的蛋白质接触图预测模型。为了验证TargetPCM的有效性,在包含98个非冗余蛋白质的数据集上进行了测试。结果表明:对于短程、中程和长程接触,TargetPCM的Top L/5精度比现有最好的集成预测器(NeBcon)分别提高了8.2%,16.1%和5.3%。在CASP11上进一步的验证表明,对于短程、中程和长程接触,TargetPCM的Top L/5精度比现有最好的基于协同进化的集成预测器(MetaPSICOV)分别提高了7.4%,9.1%和7.5%。实验结果验证了本文所提蛋白质接触图预测方法的有效性。     

Systematic centroid error compensation for the simple Gaussian PSF in an electronic star map simulator

Simulated star maps serve as convenient inputs for the test of a star sensor, whose standardability mostly depends on the centroid precision of the simulated star image, so it is necessary to accomplish systematic error compensation for the simple Gaussian PSF（or SPSF, in which PSF denotes point spread function）. Firstly, the error mechanism of the SPSF is described, the reason of centroid deviations of the simulated star images based on SPSF lies in the unreasonable sampling positions（the centers of the covered pixels） of the Gaussian probability density function. Then in reference to the IPSF simulated star image spots regarded as ideal ones, and by means of normalization and numerical fitting, the pixel center offset function expressions are got, so the systematic centroid error compensation can be executed simply by substituting the pixel central position with the offset position in the SPSF. Finally, the centroid precision tests are conducted for the three big error cases of Gaussian radius r = 0.5, 0.6, 0.671 pixel, and the centroid accuracy with the compensated SPSF（when r = 0.5） is improved to 2.83 times that of the primitive SPSF, reaching a 0.008 pixel error, an equivalent level of the IPSF. Besides its simplicity, the compensated SPSF further increases both the shape similarity and the centroid precision of simulated star images, which helps to improve the image quality and the standardability of the outputs of an electronic star map simulator（ESS）.     

考虑卫星轨道运动和像移影响的星敏感器星图模拟方法

星图模拟技术是星图识别算法和星敏感器性能测试的基础.提出一种新的高精度星图模拟方法.该方法分为三个步骤:首先,利用两行轨道数据(TLE,Two-Line Orbital Element)与简化常规/深空扰动的近似解模型(SGP4/SDP4)计算出卫星在轨运行参数,进而获得卫星姿态矩阵;然后,根据星敏感器的方位和俯仰角度,确定星敏感器视场中的导航星及星敏感器安装矩阵,利用小孔成像模型,获得导航星在星敏感器成像面的投影位置;最后,为更准确模拟实际星像点的灰度扩散,在考虑卫星运动引起的恒星像移的基础上,按照二维高斯分布规律置灰度值来模拟星像点像素.在此基础上,还详细分析了不同曝光时间下,恒星像移对恒星位置测量的影响.     

用VisualLisp动态设计建筑施工总平面图

本文介绍了一种采用VisualLisp语言对施工图进行动态绘制的方法。本文从该方法的特点、设计思想和设计过程等方面进行了论述，作为一种适用的动态绘制方法，为快速绘制建筑施工总平面图提供了一种手段。     

FMCW体制毫米波SAR实时信号处理方法研究

与脉冲体制合成孔径雷达(SAR)相比,调频连续波(FMCW)体制SAR具有体积小、重量轻、分辨率高、功耗低和低截获等一系列优点,目前小型或微小型SAR普遍采用FMCW工作体制。FMCW SAR在整个脉冲重复周期内都发射信号,其信号占空比达到了100%,为了减小数字接收机采样带宽,降低数据率,FMCW体制毫米波SAR一般采取解线频调接收的方式,但其数据量依然很大,而且机载平台受到气流的影响,运动误差很大,需要迭代估计与补偿,给实时处理模块带来了很大压力。为了提高整个机载FMCW SAR系统的信号实时处理性能,需要在算法层面进行改进。提出了一种两次子孔径误差估计和全孔径误差拼接补偿的FMCW SAR实时成像算法,使用相位梯度自聚焦(PGA)算法和图像偏置(MD)算法级联提取子孔径误差;然后进行子孔径误差拼接成全孔径误差补偿原数据,两维脉冲压缩后完成图像聚焦,提高了FMCW体制毫米波SAR成像算法的效率;最后使用机载Ka波段FMCW SAR实测数据,验证了该算法的有效性。     

叶顶间隙对离心叶轮内部流动及气动性能的影响

通过求解 N- S方程 ,数值研究了叶顶间隙对 NASA低速大尺度离心压缩机 (L SCC)三维粘性流场及气动性能的影响 ,在计算程序中采用了当地时间步长、多重网格以及隐式参差光顺来进行加速。对具有 0 .0 % ,5 0 % ,10 0 % ,2 0 0 %倍设计间隙的 4种离心叶轮的流场及气动性能进行了数值预测。研究结果表明 (1) NASA低速大尺度离心压缩机 (L SCC)半开式叶轮的低速尾迹区在压力面与轮盖的角区 ,而相应的闭式叶轮的低速尾迹区聚集在轮盖的中心位置 ;(2 )数值实验表明 ,叶顶间隙并非越小越好 ,可能存在一个最优间隙 ,使得叶轮流动损失最小