基于SMVF的高频雷达自适应多目标检测

针对高频雷达强海杂波和干扰环境下的多目标检测问题,结合S-method时频分布和Vitcrbi算法提出了一种多分量线性调频信号瞬时频率估计方法—SMVF法(S-method viterbi fitting),然后根据所提取的瞬时频率的直线拟合性能,提出了一种自适应多目标检测算法。实测数据的处理结果,表明了该算法在低信噪比时,与WDM法(wigncr distribution maxima) , WDV法( wigncr distribution vitcrbi)相比,估计精度提高约2000,验证了该算法的可行性和有效性。     

利用TrackRT进行GPS实时动态形变监测研究

在相对实时动态定位软件TrackRT的基础上进行二次开发,完善了数据流实时传输与解码,并设计了两组模拟地面运动的观测实验,分别对TrackRT水平向和垂直向上的内外符合精度进行了评定。结果表明,在观测数据质量较好的情况下,实时定位水平分量精度优于2cm,垂向分量精度优于4cm。     

矿山开采沉陷预计空间插值方法分析研究

文章首先对GIS中5种常用的空间插值方法原理进行了详细阐述,采用交叉验证法来对比分析不同插值方法的精度。应用反距离权重法、克里金法、自然邻域法、样条函数法、趋势面法5种常用的空间插值方法对兖矿集团济三煤矿1308工作面开采沉陷预计数据进行插值,对比分析了各种插值方法的精度,并对插值的误差影响因素进行了实验分析。结果表明：5种常用的空间插值方法中,克里金插值和样条函数插值精度最高,自然邻域插值和反距离权重插值精度居中,趋势面插值精度最低;对插值结果造成影响的因素与沉陷预计点的数量和密度有关,沉陷预计点的密度越大、数量越多,空间插值结果的精度就越高。研究成果可为矿山开采沉陷预计插值方法的选取提供借鉴。     

机载激光雷达数据的建筑物三维模型重建

机载激光雷达技术可以快速获取建筑物高精度高密度的三维空间信息.文章提出一种建筑物三维模型重建方法,该方法利用栅格数据使用RANSAC算法提取建筑边界上的长线段,采用规则化策略获取建筑轮廓;在模型生成阶段,基于原始点云和屋顶拓扑关系约束,获取屋顶间的交线和交点,并结合已得到的建筑边界、屋顶间交线和交点获取三维建筑模型.实验结果表明,该方法思路清晰、科学可行且适用性强,提取的建筑边界和模型垂直精度高.     

主元分析变换空间上的鉴别共同矢量人脸识别方法

给出了在主元分析(PCA)变换空间上求取DCV投影矩阵的方法(PCA+DCV),在保留所有鉴别信息的条件下,显著降低了算法复杂度,提高了运算效率。进一步提出了依据主元成分对应特征值进行适度权重的DCV识别方法(WPCA+DCV),一定程度上减小因光照、饰物遮挡等造成的面部变化带来的识别影响,增强表征信息,提高识别率。在ORL、YALE和AR人脸库上的实验结果证实了本方法的性能。     

利用NOAA-AVHRR数据分析1982-2001年间中国植被的动态变化

The authors derived the normalized difference vegetation index (NDVI) from the NOAA/AVHRR Land dataset, at a spatial resolution of 8km and 15-day intervals, to investigate the vegetation variations in China during the period from 1982 to 2001. Then, GIS is used to examine the relationship between precipitation and the Normalized Difference Vegetation Index (NDVI) in China, and the value of NDVI is taken as a tool for drought monitoring. The results showed that in the study period, China’s vegetation cover h...     

半参数模型统计诊断与粗差检验

This paper systematically studies the statistical diagnosis and hypothesis testing for the semiparametric linear regression model according to the theories and methods of the statistical diagnosis and hypothesis testing for parametric regression model.Several diagnostic measures and the methods for gross error testing are derived.Especially,the global and local influence analysis of the gross error on the parameter X and the nonparameter s are discussed in detail;at the same time,the paper proves that the d...     

Climate applications of a global, 2-hourly atmospheric precipitable water dataset derived from IGS tropospheric products

A global, 2-hourly atmospheric precipitable water (PW) dataset is produced from ground-based GPS measurements of zenith tropospheric delay (ZTD) using the International Global Navigation Satellite Systems (GNSS) Service (IGS) tropospheric products (~80–370 stations, 1997–2006) and US SuomiNet product (169 stations, 2003–2006). The climate applications of the GPS PW dataset are highlighted in this study. Firstly, the GPS PW dataset is used as a reference to validate radiosonde and atmospheric reanalysis data. Three types of systematic errors in global radiosonde PW data are quantified based on comparisons with the GPS PW data, including measurement biases for each of the fourteen radiosonde types along with their characteristics, long-term temporal inhomogeneity and diurnal sampling errors of once and twice daily radiosonde data. The comparisons between the GPS PW data and three reanalysis products, namely the NCEP-NCAR (NNR), ECMWF 40-year (ERA-40) and Japanese reanalyses (JRA), show that the elevation difference between the reanalysis grid box and the GPS station is the primary cause of the PW difference. Secondly, the PW diurnal variations are documented using the 2-hourly GPS PW dataset. The PW diurnal cycle has an annual-mean, peak-to-peak amplitude of 0.66, 0.53 and 1.11 mm for the globe, Northern Hemisphere, and Southern Hemisphere, respectively, with the time of the peak ranging from noon to late evening depending on the season and region. Preliminary analyses suggest that the PW diurnal cycle in Europe is poorly represented in the NNR and JRA products. Several recommendations are made for future improvements of IGS products for climate applications.     

Exploring uncertainty in remotely sensed data with parallel coordinate plots

The existence of uncertainty in classified remotely sensed data necessitates the application of enhanced techniques for identifying and visualizing the various degrees of uncertainty. This paper, therefore, applies the multidimensional graphical data analysis technique of parallel coordinate plots (PCP) to visualize the uncertainty in Landsat Thematic Mapper (TM) data classified by the Maximum Likelihood Classifier (MLC) and Fuzzy C-Means (FCM). The Landsat TM data are from the Yellow River Delta, Shandong Province, China. Image classification with MLC and FCM provides the probability vector and fuzzy membership vector of each pixel. Based on these vectors, the Shannon's entropy (S.E.) of each pixel is calculated. PCPs are then produced for each classification output. The PCP axes denote the posterior probability vector and fuzzy membership vector and two additional axes represent S.E. and the associated degree of uncertainty. The PCPs highlight the distribution of probability values of different land cover types for each pixel, and also reflect the status of pixels with different degrees of uncertainty. Brushing functionality is then added to PCP visualization in order to highlight selected pixels of interest. This not only reduces the visualization uncertainty, but also provides invaluable information on the positional and spectral characteristics of targeted pixels.     

计算机串口记时延迟的测量与分析

动态测量中,需要记录观测量的观测时刻,时刻作为测量的基本观测量,需要较高的计时精度,通过串口利用计算机计时是一种便捷可行的方法,但串口的时延是必须要考虑的因素。本文介绍了计算机串口计时的原理及影响其时延的相关因素,阐述了进行时延测量的方法,并通过实验对影响串口时延的5种因素进行了相应的测试和分析,实验结果表明,通常情况下串口时延在毫秒级,通过提高计时程序优先级的方法可成功将时延减小至0.35m s以内;低动态条件下串口时延对动态测量的影响较小,在某些检测设备中甚至可以忽略。