BDS不同轨道卫星精密单点定位性能分析

为了分析北斗不同轨道卫星对定位结果的影响,从而更好地利用我国自主研发的北斗卫星导航系统。该文采用亚太地区7个MGEX测站12d观测数据,进行静态、后处理动态和模拟实时动态3种模式的精密单点定位实验。实验结果表明,在北斗3类轨道卫星等权的情况下,倾斜地球同步轨道(IGSO)卫星对定位结果贡献最大;北斗两类轨道卫星组合中,IGSO+MEO组合定位精度最高,其静态精密单点定位(PPP)在E、N、U方向的RMS分别为0.62、0.39、3.71cm,后处理动态和模拟实时动态PPP的RMS为分米级;北斗各类轨道卫星与GPS组合定位中,GPS+IGSO+MEO组合定位结果收敛速度最快,收敛时间为26.30min。     

Uncertainty analysis of soil erosion modelling using different resolution of open-source DEMs

The Digital Elevation Model (DEM) is one of the important parameters of soil erosion assessment and notable uncertainties are found in using different resolutions of the DEM. Revised Universal Soil Loss Equation model has been applied to analyze the effect of open-source DEMs with different resolution and accuracy on the uncertainties of soil erosion modelling in a part of the Narmada river basin in Madhya Pradesh in central India. Selected open-source DEMs are GTOPO30 (1 km), SRTM (30 and 90 m), CARTOSAT (30 m) and ASTER (30 m), used for estimating erosion rate. Results with better accuracy are achieved with the high-resolution DEMs (30 m) with higher vertical accuracy than the coarse resolution DEMs with lower accuracy. This study has presented potential uncertainties introduced by the open-source DEMs in soil erosion modelling for better understanding of appropriate selection and acceptable errors for researchers.     

基于LBV变换的遥感影像多步骤分类法研究

面对与日俱增的遥感数据,如何快速准确地进行影像分类成为遥感领域亟待解决的问题。本文在前人的基础上提出了一种基于LBV变换的遥感影像多步骤分类方法。L:地物的总辐射水平,集中反映了裸地的信息;B:地物的可见-红外光辐射平衡,是地面水分状况和水体存在的一个良好指标;V:地物辐射随波段变化的方向和速度向量,能集中反映地面植被状况。多步骤分类法遵循由易到难的原则,能克服类别之间的互相影响,从而提高分类精度。文章结合LBV变换和多步骤分类法的优点对影像进行了分类,结果表明该方法简单易行,且能达到良好的分类精度。     

对提高导航型GPS定位精度之工作方法的探讨

论文主要介绍了导航型GPS坐标转换参数的计算方法和测量误差的改正方法。该方法的要点是通过实测多个公共点来计算坐标转换参数,以此获得较好的转换精度;并进一步对观测结果加以误差改正,从而提高其定位精度。     

基于整体最小二乘法的线性回归建模和解法

对基于自变量和因变量误差的回归问题进行了进一步研究,证明了两种方法的实质并未解决同时考虑自变量和因变量的误差问题,其解算结果和不考虑自变量误差的解算结果完全相同。给出了能同时顾及自变量和因变量误差的新的回归模型,并推导了具体的解算方法。算例结果和基于矩阵分解的整体最小二乘法解算方法的结果相同,说明了本文方法的正确性。     

GPS单点测速的误差分析及精度评价 (英文)

Error sources which decrease the accuracy of GPS in absolute velocity determination have been changed since SA was turned off. Firstly, quantities of all kinds of error sources that influence velocity determination are analyzed. The potential accuracy of GPS absolute velocity determination is derived from both theory and field GPS data simulation. After that, two tests were carried out to evaluate the performance of GPS absolute velocity determination in the case of a static and an airborne GPS receiver and INS （Inertial Navigation System） instrument in kinematic mode. In static mode, the receiver velocity has been estimated to be several mm/s with the carrier-phase derived Doppler measurements, and several cm/s with the receiver generated Doppler measurements. In kinematic mode, GPS absolute velocity estimates are compared with the synchronized measurements from the high accuracy INS. The root mean square statistics of the velocity discrepancies between GPS and INS come up to dm/s. Moreover, it has a strong correlation with the acceleration or jerk of the aircraft.     

基于高光谱Hyperion数据的线性光谱混合模型与神经网络模型的比较

混合像元问题是定量遥感中的热点问题之一,为了改进从遥感数据中提取定量信息,人们建立了各种混合光谱分解技术,其中线性光谱混合模型和神经网络模型就是两种比较成熟的方法。以陕西省横山地区的高光谱Hyperion数据为研究基础,通过最小噪声变换(MNF)、像元纯度指数(PPI)转换和RMS误差分析的迭代方法相结合提取影像中的纯净像元作为终端端元。分别运用神经网络模型和线性光谱混合模型对影像进行光谱分解,得到各个组分的分解图像。以标准植被指数(NDVI)影像为衡量标准,选取训练样本点,分别对两种模型进行回归分析,结果显示NDVI影像与线性光谱混合模型植被分解图像的判定系数(R2=0.91)要大于其与神经网络模型的判定系数(R2=0.81)。进一步分析表明在一般情况下,线性光谱混合模型具有比神经网络模型略高的分离精度,但是神经网络模型对细部信息的提取的效果要好于线性光谱混合模型,最后提出了端元均方根误差(EAR)指数,一种新的混合像元分解的思路。     

全站仪似水准法和对向法高程测量的比较研究

通过对似水准法和对向法高程测量原理、误差来源及精度的比较分析,我们发现随着距离和竖直角度的增大,对向法高程测量中误差的变化大于似水准法高程测量中误差的变化;当两观测点间的水平距离小于等于1km时,对向法高程测量精度一般高于似水准法高程测量精度,但是当两观测点间的水平距离大于1km时,似水准法高程测量精度一般高于对向法高程测量精度。     

Accuracy assessment of lidar-derived digital elevation models

Despite the relatively high cost of airborne lidar-derived digital elevation models (DEMs), such products are usually presented without a satisfactory associated estimate of accuracy. For the most part, DEM accuracy estimates are typically provided by comparing lidar heights against a finite sample of check point coordinates from an independent source of higher accuracy, supposing a normal distribution of the derived height differences or errors. This paper proposes a new methodology to assess the vertical accuracy of lidar DEMs using confidence intervals constructed from a finite sample of errors computed at check points. A non-parametric approach has been tested where no particular error distribution is assumed, making the proposed methodology especially applicable to non-normal error distributions of the type usually found in DEMs derived from lidar. The performance of the proposed model was experimentally validated using Monte Carlo simulation on 18 vertical error data-sets. Fifteen of these data-sets were computed from original lidar data provided by the International Society for Photogrammetry and Remote Sensing Working Group III/3, using their respective filtered reference data as ground truth. The three remaining data-sets were provided by the Natural Environment Research Council's Airborne Research and Survey Facility lidar system, together with check points acquired using high precision kinematic GPS. The results proved promising, the proposed models reproducing the statistical behaviour of vertical errors of lidar using a favourable number of check points, even in the cases of data-sets with non-normally distributed residuals. This research can therefore be considered as a potentially important step towards improving the quality control of lidar-derived DEMs.     

QuickBird影像制作1：10000DOM方法探讨

随着卫星遥感影像数据更加广泛地应用于测绘,针对QuickBird影像制作1：10000 DOM的方法,从正射纠正的三种不同方式进行了实验和探讨,分析了利用外业控制点或者在原有DRG、DOM上选取控制点制作DOM的方法、精度、工作量,总结提出了方便、快捷、实用的工作模式。