共查询到19条相似文献，搜索用时 156 毫秒
1.
《测绘文摘》2008,(4)
CH20081939基于方差分量估计的拟合推估及其在GIS误差纠正的应用=Variance Component Estimation Based Collocation and Its Application in GIS Error Fitting/杨元喜,张菊清,张亮(西安测绘研究所)//测绘学报.-2008,37(2).-152～157拟合推估解算必须首先求得信号向量的方差协方差矩阵,该协方差矩阵一般通过选定的协方差函数,并通过已测点数据进行拟合得到。显然观测噪声的先验方差协方差阵与拟合得到的随机信号的方差协方差矩阵必须相互协调,即观测噪声向量和信号向量的权矩阵所对应的方差因子应该一致,否则将对固定效应和随机效应参数的估计带来系统性的影响。应用方差分量估计来协调拟合推估模型中观测噪声和信号向量的随机模型,并分别从极大似然估计、MINQUE估计、赫尔默特方差分量估计三方面构建了拟合推估模型的方差分量解,最后利用新提出的理论与方法,对一幅实际的扫描地形图进行误差纠正,结果表明基于方差分量估计的拟合推估法能够提高扫描地形图的精度。图2表1参22 相似文献
2.
拟合推估法用于似大地水准面拟合时会遇到观测噪声和信号之间权比的不协调,导致观测权阵和信号向量的权矩阵比例不合理,将直接影响固定效应参数和随机信号参数的估值。当观测值含有粗差时,会使结果严重扭曲。基于此,文中将抗差Helmert方差分量估计用于似大地水准面拟合中,可自适应调整观测噪声与信号之间的权比,同时又可抵御粗差的影响。采用某山区的实测数据进行试算,外符合检验结果表明:采用自适应拟合推估法构建的似大地水准面外符合精度较正常拟合推估方法提高1cm多,且解较稳定。同时,抗差自适应拟合推估不仅有效抵御粗差的影响,而且可以调整二者权比,结果更加合理。 相似文献
3.
随机信号协方差函数的拟合和确定是拟合推估的关键。在常规协方差函数拟合时,通常假定随机信号为具有各向同性的随机过程,而事实上各向异性更具有普遍性。结合方差在不同方向的误差分量表达式,给出了各向异性协方差函数的拟合方法,利用由方差分量估计构建的自适应因子调节观测随机误差与信号对模型参数估计的贡献,以减弱观测误差和随机信号先验模型不确定而带来的影响,并将其应用于InSAR监测缺失数据填补中。计算结果表明,拟合推估具有较好的缺失数据填补能力,应用基于各向异性协方差函数的自适应拟合推估,其填补精度得到进一步的改善。 相似文献
4.
基于Helmert方差分量估计的拟合推估法及其在地图数字化误差纠正中的应用 总被引：1，自引：1，他引：0
应用拟合推估法纠正扫描获得的数字化地图的变形时,会遇到调整观测噪声与信号之间权比问题的困扰。提出一种基于Helmert方差分量估计的拟合推估算法,可以通过Helmert方差分量估计合理调整权比,保证残差分配的合理性,从而达到有效的改善空间数据质量的目标。最后通过实际计算与分析,验证上述算法的有效性。 相似文献
5.
基于各向异性的自适应拟合推估及其在缺失数据拟合中的应用 总被引：1，自引：0，他引：1
随机信号协方差函数的拟合和确定是拟合推估的关键。在常规拟合推估方法中, 通常认为随机信号具有各向同性, 而事实上各向异性现象却更为普遍。另外, 在拟合过程中, 很难保证信号协方差与观测噪声协方差的先验方差因子一致。基于此, 本文提出了基于变异函数的各向异性自适应拟合推估方法, 并将其应用于InSAR监测缺失数据的拟合。 相似文献
6.
《武汉大学学报(信息科学版)》2020,(2)
在自回归(autoregressive, AR)模型中,系数矩阵与观测向量中的随机误差同源。针对AR模型平差时观测权阵分配不合理、随机模型不准确的情况,采用变量投影法提取系数矩阵和观测向量构成的增广矩阵中的随机量,将变量误差(errors-in-variables,EIV)模型转化为非线性高斯-赫尔默特(Gauss-Helmert,GH)模型,利用非线性最小二乘理论得到一种结构总体最小二乘(structural total least squares, STLS)算法,并与最小二乘方差分量估计(least squares variance component estimation, LS-VCE)相结合推导出STLS问题的一种方差分量估计算法,将其应用到AR模型的方差分量估计。通过实测算例对算法有效性进行了验证,取得了与已有方法一致的结果。该算法观测权阵的构造十分简洁,同时也可用于协方差分量的估计。 相似文献
7.
介绍方差-协方差分量估计理论的研究和发展情况,讨论最小二乘配置模型信号与观测误差的方差分量估计问题。在实际应用中,考虑到未知参数间存在几何或物理约束,针对附有约束条件最小二乘配置的方差分量估计的问题,基于Helmert方差分量估计原理,导出相应的计算公式。模拟算例结果表明,利用约束条件能够改善方差分量的估计精度,验证方法的有效性。 相似文献
8.
在多类观测数据联合平差中,存在某类观测值的验前协方差阵正确而其他类不正确的情况,传统Helmert方差分量估计在求解此类问题时没有对正确的验前协方差阵加以区别,从而造成正确的随机模型经估计后同样也被调整。针对上述情况,首先分析了Helmert方差分量估计迭代收敛结果的实质,然后提出了随机模型基准的概念,并推导了基于随机模型基准的Helmert方差分量估计公式。经计算表明,新公式完全可行,可以用于解决实际问题。 相似文献
9.
在多类观测数据联合平差中,存在某类观测值的验前协方差阵正确而其他类不正确的情况,传统Helmert方差分量估计在求解此类问题时没有对正确的验前协方差阵加以区别,从而造成正确的随机模型经估计后同样也被调整.针对上述情况,首先分析了Helmert方差分量估计迭代收敛结果的实质,然后提出了随机模型基准的概念,并推导了基于随机模型基准的Helmert方差分量估计公式.经计算表明,新公式完全可行,可以用于解决实际问题. 相似文献
10.
11.
In collocation applications, the prior covariance matrices or weight matrices between the signals and the observations should
be consistent to their uncertainties; otherwise, the solution of collocation will be distorted. To balance the covariance
matrices of the signals and the observations, a new adaptive collocation estimator is thus derived in which the corresponding
adaptive factor is constructed by the ratio of the variance components of the signals and the observations. A maximum likelihood
estimator of the variance components is thus derived based on the collocation functional model and stochastic model. A simplified
Helmert type estimator of the variance components for the collocation is also introduced and compared to the derived maximum
likelihood type estimator. Reasonable and consistent covariance matrices of the signals and the observations are arrived through
the adjustment of the adaptive factor. The new adaptive collocation with related adaptive factor constructed by the derived
variance components is applied in a transformation between the geodetic height derived by GPS and orthometric height. It is
shown that the adaptive collocation is not only simple in calculation but also effective in balancing the contribution of
observations and the signals in the collocation model. 相似文献
12.
顾及框架点坐标误差的三维基准转换严密模型 总被引：1，自引：1，他引：0
框架点坐标是由观测数据通过平差得到的,不可避免地受到观测误差的影响。针对原框架和目标框架坐标均存在误差、非公共点与公共点间存在相关性,以及转换系数矩阵中仅部分元素存在误差的实际情况,提出了同时考虑框架内误差以及转换点间相关性的基准转换严密模型,该模型将公共点和非公共点联合处理,同时计算坐标转换参数和所有点的坐标转换值,推导出了新的严格坐标转换公式,该公式为传统坐标转换公式基础上增加一改正量的形式;进一步,推导了原框架和目标框架坐标的方差不一致情况下的坐标转换模型的自适应解法;最后,利用"陆态网络工程"2000个区域站的实测坐标进行坐标转换验证,结果表明,这种严密模型较传统坐标转换模型具有更高的坐标转换精度。 相似文献
13.
G. Fotopoulos 《Journal of Geodesy》2005,79(1-3):111-123
The well-known statistical tool of variance component estimation (VCE) is implemented in the combined least-squares (LS) adjustment of heterogeneous height data (ellipsoidal, orthometric and geoid), for the purpose of calibrating geoid error models. This general treatment of the stochastic model offers the flexibility of estimating more than one variance and/or covariance component to improve the covariance information. Specifically, the iterative minimum norm quadratic unbiased estimation (I-MINQUE) and the iterative almost unbiased estimation (I-AUE) schemes are implemented in case studies with observed height data from Switzerland and parts of Canada. The effect of correlation among measurements of the same height type and the role of the systematic effects and datum inconsistencies in the combined adjustment of ellipsoidal, geoid and orthometric heights on the estimated variance components are investigated in detail. Results give valuable insight into the usefulness of the VCE approach for calibrating geoid error models and the challenges encountered when implementing such a scheme in practice. In all cases, the estimated variance component corresponding to the geoid height data was less than or equal to 1, indicating an overall downscaling of the initial covariance (CV) matrix was necessary. It was also shown that overly optimistic CV matrices are obtained when diagonal-only cofactor matrices are implemented in the stochastic model for the observations. Finally, the divergence of the VCE solution and/or the computation of negative variance components provide insight into the selected parametric model effectiveness. 相似文献
14.
张亮 《测绘与空间地理信息》2008,31(2):145-148
抗差估计具有较好的抗拒异常观测值及粗差的能力,而最小二乘配置又能较好地处理系统误差,本文结合两者的优点,利用抗差最小二乘配置对数字化地图进行几何纠正,其中对协方差函数采用抗差拟合,得到了较好的结果。实验证明在GIS数据处理的扫描数字化地图几何纠正中,抗差最小二乘配置在抗拒异常值和处理系统误差方面优于单纯的最小二乘估计和单纯的最小二乘配置方法。 相似文献
15.
Klaus-Peter Schwarz 《Journal of Geodesy》1974,48(2):171-186
When combining satellite and terrestrial networks, covariance matrices are used which have been estimated from previous data.
It can be shown that the least-squares estimator of the unknown parameters using such an estimated covariance matrix is not
necessarily the best. There are a number of cases where a more efficient estimator can be obtained in a different way. The
problem occurs frequently in geodesy, since in least-squares adjustment of correlated observations estimated covariance matrices
are often used.
If the general structure of the covariance matrix is known, results can often be improved by a method called covariance adjustment.
The statistical model used in least-squares collocation leads to a type of covariance matrix which fits into this framework.
It is shown in which way improvements can be made using a modified approach of principal component analysis.
As a numerical example the combination of a satellite and a terrestrial network has been computed with varying assumptions
on the covariance matrix. It is shown which types of matrices are critical and where the usual least-squares approach can
be applied without hesitation. Finally, a simplified representation of covariances for spatial networks by means of a suitable
covariance function is suggested.
Paper presented at the International Symposium on Computational Methods in Geometrical Geodesy-Oxford, 2–8 September, 1973. 相似文献
16.
基于移动开窗法协方差估计和方差分量估计的自适应滤波 总被引：8，自引：1，他引：8
基于移动窗口协方差估计和方差分量估计，提出了一种新的自适应Kalman滤波技术。计算结果证实，该方法能有效地控制观测异常和载体状态扰动异常对动态系统参数估值的影响。 相似文献
17.
Helmert方差分量估计的粗差检验与抗差解 总被引：9，自引：0，他引：9
当观测值中含有粗差时，检验表明Helmert方差分量估计结果同样含有粗差，且粗差还可能会发生转移，为有效地抵制粗差和随机模型差的互相影响，指出了发生这一转移的原因，介绍了基于双因子等价权的抗差估计，并针对相关Helmert方差分量估计抗差解求解过程中容易出现的法矩阵0值溢出问题，提出了改进方法。 相似文献
18.
Khosro Moghtased-Azar Ramin Tehranchi Ali Reza Amiri-Simkooei 《Journal of Geodesy》2014,88(5):427-439
A typical problem of estimation principles of variance and covariance components is that they do not produce positive variances in general. This caveat is due, in particular, to a variety of reasons: (1) a badly chosen set of initial variance components, namely initial value problem (IVP), (2) low redundancy in functional model, (3) an improper stochastic model, and (4) data’s possibility of containing outliers. Accordingly, a lot of effort has been made in order to design non-negative estimates of variance components. However, the desires on non-negative and unbiased estimation can seldom be met simultaneously. Likewise, in order to search for a practical non-negative estimator, one has to give up the condition on unbiasedness, which implies that the estimator will be biased. On the other hand, unlike the variance components, the covariance components can be negative, so the methods for obtaining non-negative estimates of variance components are not applicable. This study presents an alternative method to non-negative estimation of variance components such that non-negativity of the variance components is automatically supported. The idea is based upon the use of the functions whose range is the set of all positive real numbers, namely positive-valued functions (PVFs), for unknown variance components in stochastic model instead of using variance components themselves. Using the PVF could eliminate the effect of IVP on the estimation process. This concept is reparameterized on the restricted maximum likelihood with no effect on the unbiasedness of the scheme. The numerical results show the successful estimation of non-negativity estimation of variance components (as positive values) as well as covariance components (as negative or positive values). 相似文献
19.
Least-squares variance component estimation 总被引：19，自引：15，他引：4
Least-squares variance component estimation (LS-VCE) is a simple, flexible and attractive method for the estimation of unknown
variance and covariance components. LS-VCE is simple because it is based on the well-known principle of LS; it is flexible
because it works with a user-defined weight matrix; and it is attractive because it allows one to directly apply the existing
body of knowledge of LS theory. In this contribution, we present the LS-VCE method for different scenarios and explore its
various properties. The method is described for three classes of weight matrices: a general weight matrix, a weight matrix
from the unit weight matrix class; and a weight matrix derived from the class of elliptically contoured distributions. We
also compare the LS-VCE method with some of the existing VCE methods. Some of them are shown to be special cases of LS-VCE.
We also show how the existing body of knowledge of LS theory can be used to one’s advantage for studying various aspects of
VCE, such as the precision and estimability of VCE, the use of a-priori variance component information, and the problem of
nonlinear VCE. Finally, we show how the mean and the variance of the fixed effect estimator of the linear model are affected
by the results of LS-VCE. Various examples are given to illustrate the theory. 相似文献