应变参数的抗差解及误差影响

应用弹性力学的应变分析理论和抗差估计原理，推导了应变参数的抗差解及其误差影响函数。实际算例表明，应变参数的抗差解可以有效地抵制粗差的异常影响，得到应变参数的可靠解，这对于利用高精度GPS复测资料研究大尺度的地壳运动和变形具有实际意义。     

一个新的GNSS模糊度估计类

介绍了一类新的GNSS模糊度估计。因为该类遵循移去一恢复原理，称之为整数等变估计类。本文将说明整数等变估计类较整数估计类和线性无偏估计类的范围要大，同时给出一个相当有用的整数等变估计类的表达式。这个表达式揭示了整数等变估计类的结构，并显示该表达式如何在浮点解的基础上实现整数等变估计。最后还提出最优整数估计。     

压缩型抗差估计

讨论了测量平差中粗差和病态性同时存在时的参数估计问题。针对抗差估计不能抗拒病态性干扰的缺点,运用有偏然计的压缩变换方法,提出了一种新的估计－压缩型抗差估计,理论分析和模拟计算表明,新估计不但能有效的减免粗差的影响,而且能显著的作病态性的干扰,是一种性能良好的估计。     

Robust bayesian estimation

Classical least squares Bayesian estimation consists of minimizing the sum of the squared residuals of observations and the corrections to prior estimates of parameters.Many authors have produced more robust versions of this estimation by replacing the square by something else, such as the absolute value. In this article, three robust (M-LS, LS-M and M-M) estimators for three corresponding error models are described based on the principle of maximum likelihood type estimates (M-estimates). The influence functions of the three robust Bayesian estimators are given. The algorithm implementation problems are discussed and the expressions for the posterior variance-covariance are derived.     

A type of biased estimators for linear models with uniformly biased data

The objective of this paper is the comparison of various types of estimators that can be used in linear models with uniformly biased data. This particular case refers to adjustment problems where the available measurements are affected by a common, unknown and uniform offset. The classic least-squares (LS) unbiased estimators for this type of models are reviewed in detail, and some additional remarks on their properties and performance are given. Furthermore, a family of biased estimators for linear models with uniformly biased data is introduced, which has the potential to provide better performance (in terms of mean squared estimation error) than the ordinary LS unbiased solutions. A number of different regularization viewpoints that can be equivalently associated with these biased estimators are presented, along with a discussion on various selection strategies that can be employed for the choice of the regularization parameter that enters into the biased estimation algorithm.     

自适应抗差最小二乘估计

抗差估计与最小二乘估计在相应条件下各具优点。特定的抗差估计极值函数只在特定的污染分布条件下显示其抗差性和优效性。本文研究最小二乘估计，抗差估计以及抗差估计类之间的自适应估计问题。重点讨论了适于测量平差计算的误差分布检验量以及自适应抗差极值函数和权函数的构造与选择，最后人出了自适应抗差最小二科解算积式。     

测量平差模型的抗差最小二乘解及影响函数

抗差Ｍ估计是使用最广泛、计算较简明的抗差估计法。基于多维Ｍ估计原理，本文建立了经典测量平差函数模型的抗差解，并推导出相应的误差影响函数；为了使抗差估计适于不同类型以及不同先验精度的各类观测值的混合平差，将使用等价权原理构造抗差最小二乘解式。     

抗差贝叶斯估计及应用

当未知参数具有先验期望和方差，且观测值与未知参数先验值均服从正态分布时，最小二乘贝叶斯估计将给出参数的最优解。然而当观测值和参数先验值的实际分布有悖于正态假设时，经典贝叶斯估计使估值偏高。本文基于常用的M估计原理，对三种类型的误差模式，导出了M－LS、LS－M和M－M三种抗差贝叶斯估计解式和影响函数；讨论了相应的计算方法；给出了参数验后方差表达式。     

自适应参数估计与内外部精度的关系

随机模型可以依据内部精度进行自适应调整,也可依据外部精度或依据半外部精度进行自适应调整。本文首先分析测量数据处理近几年发展起来的自适应参数估计统计量。分析发现,现有随机模型自适应估计都与内部精度、外部精度或半外部精度有关,进而将相应的参数估计也分为内部、外部和半外部自适应参数估计,并对这几类自适应参数估计的特点也进行了分析。最后利用算例分析这几类自适应估计的主要性质,指出这几类自适应估计的应用前提和存在的问题。     

自动建立多边形拓扑关系算法步骤的优化与改进

作者从算法和过程的效率、自动化水平和数据的完整性入手，简要分析了传统算法中存在的问题。在此基础上，以提高自动化水平为目的，将地理实体多边形拓扑关系的建立过程归结为：弧结点的匹配和弧连接关系的建立；同一结点上弧－弧拓扑关系的建立；闭合边界弧段相邻关系的建立；闭合边界包含关于的确定等主要步骤。给出了各主要步骤的算法，并对提高算法效率也提出了新的改进方案。分析与试验表明：新算法对于减少人工操作次数提高自     

Robust estimation of geodetic datum transformation

The robust estimation of geodetic datum transformation is discussed. The basic principle of robust estimation is introduced. The error influence functions of the robust estimators, together with those of least-squares estimators, are given. Particular attention is given to the robust initial estimates of the transformation parameters, which should have a high breakdown point in order to provide reliable residuals for the following estimation. The median method is applied to solve for robust initial estimates of transformation parameters since it has the highest breakdown point. A smooth weight function is then used to improve the efficiency of the parameter estimates in successive iterative computations. A numerical example is given on a datum transformation between a global positioning system network and the corresponding geodetic network in China. The results show that when the coordinates are contaminated by outliers, the proposed method can still give reasonable results. Received: 25 September 1997 / Accepted: 1 March 1999     

一种三步抗差方案的设计

抗差估计的关键是选择恰当的极值函数ρ（．）或ψ（．）函数。本文针对抗差估计涉及的几个重要问题，提出一种新的抗差方案的构想。新的抗差方案试图实现如下三阶段目标；１）选取抗差性能很强的初值，包括定位参数和单位权中误差的初值。２）综合抗差，即要求能实现系数阵空间和观测空间同时抗差，能解决相关观测抗差估计问题，实现定位参数与单位权中误差的联合抗差。３）剔除粗差，给出有关估值的准确统计特性。     

The parameter distributions of the integer GPS model

 A parameter estimation theory is incomplete if no rigorous measures are available for describing the uncertainty of the parameter estimators. Since the classical theory of linear estimation does not apply to the integer GPS model, rigorous probabilistic statements cannot be made with reference to the classical results. The fact that integer parameters are involved in the estimation process forces a reappraisal of the propagation of uncertainty. It is with this purpose in mind that the joint and marginal distributional properties of both the integer and non-integer parameters of the GPS model are determined. These joint distributions can also be used to determine the distribution of functions of the parameters. As an important example, the distribution of the vector of ambiguity residuals is determined. Received: 30 January 2001 / Accepted: 31 July 2001     

动态系统的抗差Kaliman滤波

离散历元的动态观测量及其相应的动态模型可能存在异常，若数据处理模型不考虑对这些异常的特别处理，则动态模型参数估值及其所提供的动态信息将极不可靠。基于贝叶斯统计和抗差估计原理，我们构造了一种抗差滤波算法。该算法考虑观测分布和参数验前分布均为污染分布。并利用一个实测网验算该算法和模型的可靠性。     

附有条件的参数平差模型的有偏估计

讨论附有条件的参数平差模型参数的有偏估计问题。提出了约束岭估计和约束主成分估计,并证明了它们的优良性质,最后给出了一个算例,验证了所得结果。     

基于偏差矫正的有偏估计及其在GPS快速定位中的应用

基于偏差矫正的一般理论提出了不适定问题的新的有偏估计。在病态条件下,Gauss-Markov模型参数的最优线性无偏估计,即LS估计是不稳健的,所得估值方差较大,严重偏离真值。因此,文中放弃了对参数估计无偏性的限制,考虑有偏估计的偏差,结合偏差矫正的正则化解法的一般理论提出了一种新的基于偏差矫正的有偏估计;结合岭估计中参数的选择方法确定了替代矩阵。最后通过GPS动态定位算例,验证了新估计的稳定性和有效性。     

稳健估计的一种改进迭代算法

当观测值不含粗差、观测误差服从零均值分布时,最小二乘算法是最优无偏估计。若观测值包含粗差,由于最小二乘不具备抗差性,往往采用以M估计为代表的稳健估计方法,选权迭代算法是应用最为广泛的稳健估计方法之一。目前,选权迭代算法的每一步都需要对模型的稳健正交矩阵求逆,其运算复杂度是矩阵维数的三次方,在未知参数或粗差个数较多的情况下,计算量大、计算时间长。本文基于矩阵逆的运算法则,对现有选权迭代算法进行了改进,改进的选权迭代算法在迭代计算过程中仅需计算更新权阵后的解的改正项,不需要对正交矩阵求逆,显著提高了算法的效率。     

An optimality property of the integer least-squares estimator

A probabilistic justification is given for using the integer least-squares (LS) estimator. The class of admissible integer estimators is introduced and classical adjustment theory is extended by proving that the integer LS estimator is best in the sense of maximizing the probability of correct integer estimation. For global positioning system ambiguity resolution, this implies that the success rate of any other integer estimator of the carrier phase ambiguities will be smaller than or at the most equal to the ambiguity success rate of the integer LS estimator. The success rates of any one of these estimators may therefore be used to provide lower bounds for the LS success rate. This is particularly useful in case of the bootstrapped estimator. Received: 11 January 1999 / Accepted: 9 July 1999     

On the probability density function of the GNSS ambiguity residuals

Integer GNSS ambiguity resolution involves estimation and validation of the unknown integer carrier phase ambiguities. A problem then is that the classical theory of linear estimation does not apply to the integer GPS model, and hence rigorous validation is not possible when use is made of the classical results. As with the classical theory, a first step for being able to validate the integer GPS model is to make use of the residuals and their probabilistic properties. The residuals quantify the inconsistency between data and model, while their probabilistic properties can be used to measure the significance of the inconsistency. Existing validation methods are often based on incorrect assumptions with respect to the probabilistic properties of the parameters involved. In this contribution we will present and evaluate the joint probability density function (PDF) of the multivariate integer GPS carrier phase ambiguity residuals. The residuals and their properties depend on the integer estimation principle used. Since it is known that the integer least-squares estimator is the optimal choice from the class of admissible integer estimators, we will only focus on the PDF of the ambiguity residuals for this estimator. Unfortunately the PDF cannot be evaluated exactly. It will therefore be shown how to obtain a good approximation. The evaluation will be completed by some examples.