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顾及像点观测方程的系数矩阵中存在随机误差,提出了基于总体最小二乘的线阵卫星遥感影像光束法平差模型。在假定像点观测误差和系数矩阵误差均为独立、等精度分布的基础上,利用拉格朗日条件极值法推导了包含外方位元素虚拟观测方程和控制点误差方程的总体最小二乘光束法平差算法的具体公式和计算方法。该方法利用方差分量估计确定各类虚拟观测值的方差,可求解包含多类虚拟观测量的平差问题,并可用先验信息或岭迹法确定系数矩阵观测值的权比例系数,从而克服了现有总体最小二乘虚拟观测方法不能处理多类虚拟观测值的不足,确保了光束法平差可正确有效求解。分别利用模拟算例与两组真实影像进行了试验验证。结果表明,相比于常规最小二乘虚拟观测法以及现有总体最小二乘虚拟观测方法,本文方法具有更高的求解精度与适应性。相较于传统线阵卫星遥感影像光束法平差方法,本文方法可以获得更高的平差计算精度。 相似文献
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《测绘科学技术学报》2013,(2)
运用GPS/GLONASS组合导航时,由于卫星系统的测距精度不同,需要在组合解算中采用方差分量估计进行合理定权和平差计算。但是,当GPS和GLONASS观测值中含有粗差时,若采用最小二乘方差分量估计则无法抵抗粗差的影响,从而降低平差结果的精度和可靠性。为了提高GPS/GLONASS组合解算的抗差性,本文引入了基于IGGⅢ等价权函数的抗差估计方法,经过对GPS/GLONASS实测数据的计算和分析,证明这是一种可行的和有效的方法。 相似文献
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传统的后方交会最小二乘解法需要良好的外方位元素初值。在无初值或者初值不够精确的情况下,最小二乘迭代不容易收敛。在近景摄影测量或者计算机视觉等领域,往往不提供良好的初值,无法适用传统的后方交会解法。针对上述情况,本文提出了一种基于单应性矩阵的后方交会直接解法,在不需要初值的情况下,获取外方位元素的直接解。该方法根据单应性矩阵所描述的平面几何关系,利用单应性矩阵内在的约束条件,将后方交会问题转换为一个二元二次方程组的求解问题。该方法受舍入误差影响小,在无偶然误差的情况下,解算精度能达到10–9量级,能够避免传统直接解法计算复杂的问题,为传统的平差迭代解法提供良好的初值。此外,在多个控制点共面的情况下,该方法能够直接获得外方位元素的精确解。实验结果表明:在各种不同倾角拍摄的情况下,该方法均能够获得稳定的外方位元素,为后续的后方交会最小二乘算法提供良好的初值。采用本文方法计算的初值参与平差,能够达到与人工给定初值平差一致的精度,且迭代收敛速度是人工给定初值平差的2倍以上。在控制点共面的情况下,该方法的反投影精度能够达到亚像素级,且精度优于大部分主流的直接解法。 相似文献
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介绍了近代平差理论的稳健估计方法,编制稳健估计方法的程序,并通过实例验证,与最小二乘估计进行比较,表明稳健估计在水准网粗差探测和平差计算中优于最小二乘估计方法,并且能够定位粗差,从而进行消除或者减弱,得到较为干净的观测值。因此,稳健估计方法应用于测量平差具有一定的抵抗粗差的能力,从而可以提高数据处理的精度。 相似文献
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合理的参数估计及精度评定不仅需要可靠的函数模型，而且需要正确的随机模型。从权函数和粗差编辑两方面，研究了不同随机模型对西安流动卫星激光测距（satellite laser ranging，SLR）站坐标解算的影响，采用全球Lageos-1卫星观测数据计算了西安流动SLR站坐标。计算结果表明:①西安流动SLR站的观测精度和坐标解算精度均达到厘米级。②随机模型直接影响SLR站坐标的解算结果及可靠性；对于相同的计算弧段，抗差方差分量估计得到的站坐标精度最高、结果最稳定，残差加权均方差最小，观测资料利用率也最高；对于相同的计算方案，采用的SLR数据越多，坐标估计精度越高。 相似文献
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BDS/GPS/GLONASS组合系统定位时,由于系统间卫星测距精度的差异性,需要合理确定卫星间权比,Helmert方差分量估计常被用于确定不同类观测值间权比;而当观测值含有粗差时,Helmert方差分量估计定位结果容易被粗差污染或收敛失真,出现大的偏差。文中基于Helmert方差分量估计,引入等价权因子IGGIII函数,建立抗差Helmert方差分量估计权函数模型,对比分析其在低截止高度角10°、15°和20°下,在BDS/GPS/GLONASS组合系统定位中的应用及定位精度,并讨论分析在高截止高度角30°和40°下,组合系统和单系统BDS的定位精度。实验结果表明:当观测值无明显粗差时,Helmert方差分量估计和抗差分量估计的定位精度相当,略低于高度角权函数的定位结果,点位精度RMS优于2.5m;含粗差时,抗差解定位精度最高;当截止高度角为30°时,BDS单系统定位精度RMS优于5m,而组合系统RMS接近3m;为40°时,组合系统平面精度RMS优于2m,三维精度RMS优于6m,而单系统不能定位。 相似文献
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克服经典平差线性化的不足,将遗传算法理论引入卫星影像的空间后方交会解算中,利用遗传算法全局和局部搜索力强的优势,求解IKONOS影像和模拟影像的单片空间后方交会病态问题。实验结果表明,遗传算法可以有效求得精度较高的最优解;同时,相比最小二乘、岭估计等方法,其运行效率也较高。 相似文献
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由载波相位观测值直接解算姿态能实现观测及姿态约束信息的最优利用。本文推导了基于失准角及乘性误差四元数的载波相位观测模型,分别建立了有外部角速度传感器和无外部传感器辅助下姿态参数估计的状态模型;利用自适应抗差滤波估计姿态误差,借鉴分类自适应因子的思想,分别确定模糊度和姿态误差参数的自适应因子,其中姿态自适应因子由Ratio值构造的三段函数确定。自适应抗差滤波能够充分利用约束信息和历史信息,将其融合在浮点解计算过程中,极大提高模糊度浮点解精度及其协方差的结构,在此基础上使用整数最小二乘模糊度降相关平差法(least-squares ambiguity decorrelation adjustment,LAMBDA)方法即能快速搜索出固定解,满足实时性需求。采用实测舰载GNSS 3天线测姿算例对方法进行了验证,结果表明,基于自适应抗差滤波的观测值直接定姿方法效率高、可靠性好。 相似文献
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Variance component estimation uncertainty for unbalanced data: application to a continent-wide vertical datum 总被引：2，自引：2，他引：0
Variance component estimation (VCE) is used to update the stochastic model in least-squares adjustments, but the uncertainty associated with the VCE-derived weights is rarely considered. Unbalanced data is where there is an unequal number of observations in each heterogeneous data set comprising the variance component groups. As a case study using highly unbalanced data, we redefine a continent-wide vertical datum from a combined least-squares adjustment using iterative VCE and its uncertainties to update weights for each data set. These are: (1) a continent-wide levelling network, (2) a model of the ocean’s mean dynamic topography and mean sea level observations, and (3) GPS-derived ellipsoidal heights minus a gravimetric quasigeoid model. VCE uncertainty differs for each observation group in the highly unbalanced data, being dependent on the number of observations in each group. It also changes within each group after each VCE iteration, depending on the magnitude of change for each observation group’s variances. It is recommended that VCE uncertainty is computed for VCE updates to the weight matrix for unbalanced data so that the quality of the updates for each group can be properly assessed. This is particularly important if some groups contain relatively small numbers of observations. VCE uncertainty can also be used as a threshold for ceasing iterations, as it is shown—for this data set at least—that it is not necessary to continue time-consuming iterations to fully converge to unity. 相似文献
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Witold Prószyński 《Journal of Geodesy》2013,87(1):89-99
The paper presents an approach to internal reliability analysis of observation systems known as Errors-in-Variables (EIV) models with parameters estimated by the method of least squares. Such problems are routinely treated by total least squares adjustment, or orthogonal regression. To create a suitable environment for derivations in the analysis, a general nonlinear form of such EIV models is assumed, based on a traditional adjustment method of condition equations with unknowns, also known as the Gauss–Helmert model. However, in order to apply the method of reliability analysis based on the approach to response assessment in systems with correlated observations, presented in the earlier work of this author, it was necessary to confine the considerations to a quasi-linear form of the Gauss–Helmert model, representing quasi-linear EIV models. This made it possible to obtain a linear disturbance/response relationship needed in that approach. Several specific cases of quasi-linear EIV models are discussed. The derived formulas are consistent with those already functioning for standard least squares adjustment problems. The analysis shows that, as could be expected, the average level of response-based reliability for such EIV models under investigation is lower than that for the corresponding standard linear models. For EIV models with homoscedastic and uncorrelated observations, the relationship between the average reliability indices for the independent and the dependent variables is formulated for multiple regression and coordinate transformations. Numerical examples for these two applications are provided to illustrate this analysis. 相似文献
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The variance component estimation (VCE) method as developed by Helmert has been applied to the global SLR data set for the year 1987. In the first part of this study the observations have been divided into two groups: those from ruby and YAG laser systems, and their weights estimated over several months. It was found that the weights of both sets of stations altered slightly from month to month, but that, not surprisingly, the YAG systems consistently outperformed those based on ruby lasers. The major part of this paper then considers the estimation of the variance components (i.e. weights) at each SLR station from month to month. These were tested using the F-statistic and, although it indicated that most stations had significant temporal variations, they were generally small compared with the differences between the stations themselves, i.e. the method has been shown to be capable of discriminating between the precision with which the various laser stations are operating. The station coordinates and baseline lengths computed using both a priori, and estimated, weights where also compared and this showed that changes in the weights can have significant effects on the estimation of the station positions, particularly in the z component, and on the baseline lengths - so proving the importance of proper stochastic modelling when processing SLR data. 相似文献
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William H. Sprinsky 《Journal of Geodesy》1978,52(4):269-279
In a least squares adjustment (a minimum variance solution) using the technique of variation of coordinates (observation equations),
a key result is the co-variance (dispersion) matrix of parameters. Assuming that standard errors of observations are used
in the formation of the normal equations, rather than relative weights, this dispersion matrix gives the estimates of standard
errors for the parameters solved for in the adjustment. A method will be presented which allows the designer of the observing
plan to alter this dispersion matrix, which may not meet user requirements, so that it will meet user requirements and, from
its inverse, solve mathematically for the selection and quality (accuracy) of the observations required to form this altered
dispersion matrix of parameters. 相似文献
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复数域最小二乘平差及其在POLInSAR植被高反演中的应用 总被引：2，自引：1，他引：1
传统的测量观测值都是实数,因此测量平差都是在实数空间中进行的。然而,随着科学技术的快速发展,现代测绘领域中出现了一些用复数表示的观测数据。与实数数据一样,这些复数数据同样面临着如何从带有误差的观测值中找出未知量的最佳估计值的问题。但目前涉及复数观测的数据处理时,主要还是依据观测过程,分步或直接解算,不能考虑观测误差、多余观测信息等。针对这一情况,本文介绍了复数域中数据处理的最小二乘方法,试图将测量平差从实数域推广到复数域,并定量研究了两种平差准则的优劣性。为了了解复数域最小二乘的有效性,本文以极化干涉SAR植被高反演为例,建立复数域平差函数模型和随机模型,构建复数域最小二乘法反演植被高。结果表明该算法反演的植被高结果可靠,其精度优于经典植被高反演算法,且计算简单,易于实现。 相似文献
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1st0pt在沉降预测中的应用研究 总被引：1，自引：1，他引：0
预测方法有多种,找一种操作简单的方法较难。本文利用综合优化软件包1 st0pt,选用几种预测模型,通过对实测数据进行拟合,得出各种预测方法的计算模型,再利用最小二乘法原理,以预测绝对误差平方和最小为目标,给每种预测模型赋予不同的权重,组成规划方程,求出权重数列并组成新的预测模型,再对建筑物进行预测,将得到较好的预测结果。 相似文献
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在精密单点定位技术中,伪距与载波相位在两者权比一般为固定常数,这与实际不符.由于伪距和载波两类观测值的精度不一致,因此合理的定权是提高定位精度的关键.同时,当观测值中含有粗差时,将使定位结果严重失真.本文将抗差Helmert方差分量估计引入中,采用IGS站bjfs站的实测数据进行定位,结果表明,抗差Helnert方差分... 相似文献
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Helmert方差分量估计方法已被广泛用于测量平差观测量的定权中,但是,实际应用中该方法却存在不收敛的现象。为此,将信息熵和变异系数引入测量平差,提出了2种新的处理不同类型观测量、同类型不同精度观测值、甚至同类型同精度观测值进行定权的方法。数值实验表明,提出的方法效果优于Helmert方法。 相似文献
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变量误差（error-in-variables，EIV）模型的系数矩阵存在结构特征的情况，并且这种结构特征可以扩展到观测向量中。首先采用变量投影法将系数矩阵的增广矩阵展开成仿射矩阵形式，提取系数矩阵和观测向量中的随机量，并将EIV模型表示为非线性高斯-赫尔默特模型，然后利用非线性最小二乘原理推导了一种结构总体最小二乘法。该算法统一了普通的结构总体最小二乘法、结构数据最小二乘法以及最小二乘法。将该算法应用到真实算例和模拟算例中，两个算例结果表明，该算法与已有能够解决EIV模型结构特征的结构或加权总体最小二乘法估计结果一致，验证了该算法的有效性。同时，该算法对结构特征的提取方式简单、规律性强且易于编程实现；且在算法设计中，把结构总体最小二乘问题转换为附有参数的条件平差问题，即将其纳入到最小二乘平差理论体系，便于其扩展应用。同时对平面拟合问题的误差估计特性进行了定性分析，由分析可知参数的相对大小对估计误差的一致性有直接影响，这说明EIV模型下系数矩阵和观测向量中随机量的估计误差与真误差的一致性关系相对复杂。 相似文献