双步抗差估计及其应用

抗差估计是一种可以有效抵制粗差影响的平差方法。但权因子函数的临界值定值问题较为困难,若选取不当,会造成法方程系数阵秩亏或粗差观测值的影响未能完全消除,从而导致平差无法进行或抗差不彻底。针对上述问题提出了一种改进型抗差估计法一双步抗差估计法,并通过对一边角网和一实测GPS向量网进行的试算,验证了双步抗差估计的优越性。     

卧虎山水库不同算法LS因子值适用性分析

在总结以往LS因子相关算法研究基础上,结合McCool的LS因子参照值,对LS算法的适用性进行评价分析。研究表明,除去复合算法和Remortel修正算法外,其他不同算法LS因子值都小于参照值;研究区LS因子值的最优算法为基于Remortel迭代运算的修正算法;其次为结合刘宝元的陡坡公式和Remortel改进L指数因子迭代运算的复合算法,以及Remortel第4版AML程序算法;再次为B?hner算法,而Moore算法和Desmet算法,由于其与参照值的相关性相对较差,而且其RMSE相对较大,不推荐在该区使用。     

A theoretical study on terrestrial gravimetric data refinement by Earth gravity models

The idea of this paper is to present estimators for combining terrestrial gravity data with Earth gravity models and produce a high‐quality source of the Earth's gravity field data through all wavelengths. To do so, integral and point‐wise estimators are mathematically developed, based on the spectral combination theory, in such a way that they combine terrestrial data with one and/or two Earth gravity models. The integral estimators are developed so that they become biased or unbiased to a priori information. For testing the quality of the estimators, their global mean square errors are generated using an Earth gravity model08 model and one of the recent products of the gravity field and steady‐state ocean circulation explorer mission. Numerical results show that the integral estimators have smaller global root mean square errors than the point‐wise ones but they are not efficient practically. The integral estimator of the biased type is the most suited due to its smallest global root mean square error comparing to the rest of the estimators. Due largely to the omission errors of Earth gravity models the point‐wise estimators are not sensitive to the Earth gravity model commission error; therefore, the use of high‐degree Earth gravity models is very influential for reduction of their root mean square errors. Also it is shown that the use of the ocean circulation explorer Earth gravity model does not significantly reduce the root mean square errors of the presented estimators in the presence of Earth gravity model08. All estimators are applied in the region of Fennoscandia and a cap size of 2° for numerical integration and a maximum degree of 2500 for generation of band‐limited kernels are found suitable for the integral estimators.     

采用变系数回归模型提取GPS坐标序列季节性信号

提出采用变系数回归模型提取连续GPS坐标序列中包含的振幅时变季节性信号。对模拟数据及实际GPS坐标序列两组数据的分析结果表明,变系数回归模型在提取GPS坐标序列季节信号方面比传统模型更有效。经处理,GPS坐标序列能获得更合理的速度及噪声估计。     

测流不确定度的插值方差估计法

目前,测流不确定度通过误差试验或通过经验数值来确定,但这些方式存在着工作量大或不确定估计不足等局限性。为解决此问题,对基于实测数据和统计理论的插值方差估计法在不同测流条件下进行了验证,选取白河、襄阳和沙洋3个流量站进行了实测数据的不确定度分析,同时对白河站进行了Monte Carlo试验,比较插值方差估计法得到的不确定度与真实误差的差异。结果表明,插值方差估计法能较好地反映水位变化的影响,插值方差估计法所得到的不确定度与真实测流误差的相关系数达0.64,与断面水位变化的Spearman相关系数达0.79,高、中水位情况下插值方差估计法的不确定度估计结果较为合理,低水位情况下偏高。     

广义非线性动态处理模型及其解算方法

本文针对当今各国高层领导和科学家十分关注并大力倡导的“数字地球”、“数字国家”、“数字城市”、“数字矿山”等科学工程构建中遇到的大量的多源、多维、多类型、多时态、多精度并具有非线性特征的联合数据处理问题的特点,建立了一个广义非线性动态联合数据处理模型及其相应的广义非线性最小二乘模型。针对该模型规模大、维数高的特点,借鉴多变量函数寻优的“变量轮换法”或“因素交替法”的思想、结合无记忆牛顿法,建立了一个解算算法,该算法将大规模的优化问题分解为两个较低规模的优化问题进行解算,降低了问题的规模,借助无记忆牛顿法,减少了存储量,特别适合大规模问题的解算。     

Estimation of rainfall elasticity of streamflow in Australia

Abstract

Estimates of rainfall elasticity of streamflow in 219 catchments across Australia are presented. The rainfall elasticity of streamflow is defined here as the proportional change in mean annual streamflow divided by the proportional change in mean annual rainfall. The elasticity is therefore a simple estimate of the sensitivity of long-term streamflow to changes in long-term rainfall, and is particularly useful as an initial estimate of climate change impact in land and water resources projects. The rainfall elasticity of streamflow is estimated here using a hydrological modelling approach and a nonparametric estimator. The results indicate that the rainfall elasticity of streamflow (? _P ) in Australia is about 2.0–3.5 (observed in about 70% of the catchments), that is, a 1% change in mean annual rainfall results in a 2.0–3.5% change in mean annual streamflow. The rainfall elasticity of streamflow is strongly correlated to runoff coefficient and mean annual rainfall and streamflow, where streamflow is more sensitive to rainfall in drier catchments, and those with low runoff coefficients. There is a clear relation-ship between the ? _P values estimated using the hydrological modelling approach and those estimated using the nonparametric estimator for the 219 catchments, although the values estimated by the hydrological modelling approach are, on average, slightly higher. The modelling approach is useful where a detailed study is required and where there are sufficient data to reliably develop and calibrate a hydrological model. The nonparametric estimator is useful where consistent estimates of the sensitivity of long-term streamflow to climate are required, because it is simple to use and estimates the elasticity directly from the historical data. The nonparametric method, being model independent, can also be easily applied in comparative studies to data sets from many catchments across large regions.     

The success rate and precision of GPS ambiguities

 An application of a theorem on the optimality of integer least-squares (LS) is described. This theorem states that the integer LS estimator maximizes the ambiguity success rate within the class of admissible integer estimators. This theorem is used to show how the probability of correct integer estimation depends on changes in the second moment of the ambiguity `float' solution. The distribution of the `float' solution is considered to be a member of the broad family of elliptically contoured distributions. Eigenvalue-based bounds for the ambiguity success rate are obtained. Received: 11 January 1999 / Accepted: 2 November 1999     

平衡损失下回归系数stein压缩估计的性质

在平衡损失风险函数准则下,研究线性模型中回归系数的stein估计优于最小二乘估计(LS)的充分必要条件,然后在pitman closeness(PC)准则下比较了stein估计相对于最小二乘估计的优良性。