共查询到20条相似文献，搜索用时 15 毫秒
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在平面四参数坐标转换模型中,观测向量和误差方程系数矩阵中部分元素都存在误差。提出一种使用整体最小二乘迭代法求解坐标转换四参数的新方法,只改正系数矩阵中含误差的元素,同时使系数矩阵中不同位置的相同元素具有相同改正数,理论上更严谨。设计了平面四参数模型坐标转换实验数据,通过与经典最小二乘、整体最小二乘、混合整体最小二乘3种方法结果对比,验证了新方法的可行性且解算结果更优。 相似文献
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在测量数据处理中,最为经典的处理方法是最小二乘法,认为误差只是包含在观测向量当中,系数矩阵中不包含误差。实际上由于模型等因素,系数矩阵中经常存在着误差。为了平差的严密性和精确性,采用一种可以同时顾及观测向量误差和系数矩阵误差的总体最小二乘方法,应用于测量数据处理和坐标转换中,得到更符合实际的平差处理,获得更准确的坐标转换参数。 相似文献
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不同空间坐标系在进行坐标转换过程中,利用整体最小二乘(TLS)构建高斯-马尔科夫(Gauss-Markov)模型求解布尔莎-沃尔夫(Bursa-Wolf)七参数模型时,存在已知控制点含有粗差、模型系数阵固定常数参与残差改正的问题。通过对系数矩阵中含误差参数进行改正,并结合稳健估计的方法,对TLS进行迭代定权,解决了已知控制点粗差会对参数计算精度产生影响的问题,同时使得系数矩阵中非常数项得到精确的残差改正。本文通过实验数据证明,此方法可行并且解算精度更优。 相似文献
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针对传统的三维坐标转换模型局限于求解小旋转角的三维坐标转换参数的缺点,以及没有同时顾及观测向量和系数矩阵的随机误差,该文提出了一种新的三维坐标转换参数求解模型。基于非线性Gauss-Helmert模型,建立了三维坐标转换的Bursa-Wolf模型,采用Newton-Gauss迭代算法,构建了加权整体最小二乘问题的拉格朗日函数,并给出了该算法的具体推导过程及其精度评定公式。实测数据和仿真数据结果表明:新算法在无须假设条件的前提下,可以获得任意旋转角下的坐标转换参数,且待估参数数目大大降低,易于程序实现。 相似文献
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Parameter estimation in 3D affine and similarity transformation: implementation of variance component estimation 总被引：1，自引：0，他引：1
A. R. Amiri-Simkooei 《Journal of Geodesy》2018,92(11):1285-1297
Three-dimensional (3D) coordinate transformations, generally consisting of origin shifts, axes rotations, scale changes, and skew parameters, are widely used in many geomatics applications. Although in some geodetic applications simplified transformation models are used based on the assumption of small transformation parameters, in other fields of applications such parameters are indeed large. The algorithms of two recent papers on the weighted total least-squares (WTLS) problem are used for the 3D coordinate transformation. The methodology can be applied to the case when the transformation parameters are generally large of which no approximate values of the parameters are required. Direct linearization of the rotation and scale parameters is thus not required. The WTLS formulation is employed to take into consideration errors in both the start and target systems on the estimation of the transformation parameters. Two of the well-known 3D transformation methods, namely affine (12, 9, and 8 parameters) and similarity (7 and 6 parameters) transformations, can be handled using the WTLS theory subject to hard constraints. Because the method can be formulated by the standard least-squares theory with constraints, the covariance matrix of the transformation parameters can directly be provided. The above characteristics of the 3D coordinate transformation are implemented in the presence of different variance components, which are estimated using the least squares variance component estimation. In particular, the estimability of the variance components is investigated. The efficacy of the proposed formulation is verified on two real data sets. 相似文献
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ABSTRACT In this paper, we propose a method to regenerate Rational Polynomial Coefficients (RPCs) using KOMPSAT-3A imagery and to reduce the geolocation error using minimum ground control points (GCPs). To estimate the new RPCs, the physical sensor model fitted to KOMPSAT-3A imagery was utilized and virtual GCPs over the study area were created. The size of the virtual grid used was 20x20x20. To remove the sensor-related errors in physical sensor model, three different image correction models (image coordinate translation model, shift and drift model, and affine transformation model) were additionally applied. We evaluated our proposed method in two areas within Korea, one in urban (Seoul) and one in rural (Goheung) areas. The results showed that there was a significant improvement after applying the suggested approach in the two areas. The image coordinate translation model is suggested in terms of GCP requirement and expected errors estimated from the error propagation analysis using Gauss–Markov Model (GMM). 相似文献
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Although total least squares (TLS) is more rigorous than the weighted least squares (LS) method to estimate the parameters in an errors-in-variables (EIV) model, it is computationally much more complicated than the weighted LS method. For some EIV problems, the TLS and weighted LS methods have been shown to produce practically negligible differences in the estimated parameters. To understand under what conditions we can safely use the usual weighted LS method, we systematically investigate the effects of the random errors of the design matrix on weighted LS adjustment. We derive the effects of EIV on the estimated quantities of geodetic interest, in particular, the model parameters, the variance–covariance matrix of the estimated parameters and the variance of unit weight. By simplifying our bias formulae, we can readily show that the corresponding statistical results obtained by Hodges and Moore (Appl Stat 21:185–195, 1972) and Davies and Hutton (Biometrika 62:383–391, 1975) are actually the special cases of our study. The theoretical analysis of bias has shown that the effect of random matrix on adjustment depends on the design matrix itself, the variance–covariance matrix of its elements and the model parameters. Using the derived formulae of bias, we can remove the effect of the random matrix from the weighted LS estimate and accordingly obtain the bias-corrected weighted LS estimate for the EIV model. We derive the bias of the weighted LS estimate of the variance of unit weight. The random errors of the design matrix can significantly affect the weighted LS estimate of the variance of unit weight. The theoretical analysis successfully explains all the anomalously large estimates of the variance of unit weight reported in the geodetic literature. We propose bias-corrected estimates for the variance of unit weight. Finally, we analyze two examples of coordinate transformation and climate change, which have shown that the bias-corrected weighted LS method can perform numerically as well as the weighted TLS method. 相似文献
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对三维坐标转换的高斯-赫尔默特（Gauss-Helmert,GH）模型,采用牛顿-高斯（Newton-Gauss）迭代算法构建了该模型的拉格朗日目标函数,推导了其解算方法,并给出了具体的计算步骤。在此基础上,考虑到可能出现的粗差对观测空间与结构空间的综合影响,基于标准化残差构造权因子函数,推导了该模型的抗差解法。仿真实验结果表明,GH模型用于三维坐标转换时不受旋转角度大小和其他附加条件限制,解算结果与现有算法一致,且估计参数的维数大大降低,计算效率有一定程度的提高;所提出的抗差解法效果良好,与现有基于整体最小二乘的三维坐标转换的抗差解法相比,表现出了更好的稳健性。 相似文献
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三维坐标转换参数求解的一种直接搜索法 总被引：1，自引：0，他引：1
采取了两步措施简化三维坐标转换非线性模型:①旋转矩阵的3个旋转角用一个反对称矩阵的3个独立元素代替,将旋转矩阵由反对称矩阵构成Lodrigues矩阵;②将坐标转换7参数模型变换成基线向量模型,消去平移3参数.然后,采用遗传算法与模式搜索法相结合的一种直接搜索法求解参数.算例表明,该算法是可行的.最后,从坐标转换精度的角度时基线向量模型原点与公共点的选取进行了分析,结论是原点选取的点的精度相对较高时坐标转换精度相对较高,公共点的选取以3～5个精度高的点为宜. 相似文献
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平面四参数坐标转换模型具有计算方便和模型精度高等特点，已广泛应用于不同平面坐标系成果的转换。大量的研究成果提高了模型的精度和适用范围，而忽视了高精度转换成果对参数保密的影响。针对转换参数的保密需求，则有必要分析参数反算的精度及其控制方法。本文首先推导了转换模型的内符合误差和外推误差；然后分别采用无误差和有误差的原始转换参数对坐标成果进行转换，并对转换后的成果附加不同的坐标误差；最后选择不同分布和数量的坐标点参与转换参数反算，从而分析不同方案参数反算的精度。试验结果表明，参数反算的精度可以通过增加转换点的数量和扩大其转换范围得到不断的提高，最高能达到原始转换参数的精度。因此，参数保密的有效方式为首先需要降低原始转换参数精度；然后根据转换成果的分布范围、数量及精度应用需求，对坐标成果附加不同的误差，从而达到参数保密的效果。 相似文献
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On symmetrical three-dimensional datum conversion 总被引：2，自引：0，他引：2
A 3-D similarity transformation is frequently used to convert GPS-WGS84-based coordinates to those in a local datum using
a set of control points with coordinate values in both systems. In this application, the Gauss-Markov (GM) model is often
employed to represent the problem, and a least-squares approach is used to compute the parameters within the mathematical
model. However, the Gauss–Markov model considers the source coordinates in the data matrix (A) as fixed or error-free; this is an imprecise assumption since these coordinates are also measured quantities and include
random errors. The errors-in-variables (EIV) model assumes that all the variables in the mathematical model are contaminated
by random errors. This model may be solved using the relatively new total least-squares (TLS) estimation technique, introduced
in 1980 by Golub and Van Loan. In this paper, the similarity transformation problem is analyzed with respect to the EIV model,
and a novel algorithm is described to obtain the transformation parameters. It is proved that even with the EIV model, a closed
form Procrustes approach can be employed to obtain the rotation matrix and translation parameters. The transformation scale
may be calculated by solving the proper quadratic equation. A numerical example and a practical case study are presented to
test this new algorithm and compare the EIV and the GM models. 相似文献
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为提高三维坐标转换参数的求解质量,本文基于最优化算法提出了一种稳健的公共点加权坐标转换方法。以坐标转换后公共点的点位残差加权平方和最小为目标函数,利用Nelder-Mead单纯形直接搜索算法,寻找公共点坐标分量在解算坐标转换参数时的最优权重组合。以粒子加速器磁铁的准直安装为应用场景,利用模拟数据和实测数据对本文方法进行验证。结果表明:本文方法能够有效降低粗差观测值及质量不佳观测值的权重。与最小二乘、抗差估计等方法相比,本文方法解算结果的点位残差加权平方和更小,坐标转换参数质量更优。本文方法能提高三维坐标转换参数的求解质量,尤其适用于验前精度未知、观测数据质量不佳的情况。 相似文献
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针对Bursa模型在坐标系转换时没有顾及局部变形和累积误差的问题,通过对坐标转换误差进行分析,本文提出将由此产生的系统误差看作非参数信号的半参数估计,采用半参数模型对某一区域坐标进行解算,并对检核点非参数分量进行推估,与Bursa模型进行比较,结果表明半参数模型能够有效地消除系统误差。并探讨了不同确定平滑因子α的方法对坐标转换精度影响,计算结果表明,在正则矩阵R相同情况下,不同平滑因子确定方法得到的坐标转换精度有所不同,但均优于Bursa模型转换精度。 相似文献
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