卡尔曼滤波在滑坡监测中的应用

针对滑波变形的特点,将滑坡体上的监测点视为一运动点场,提出一种以运动方程为核心、以卡尔曼滤波技术为工具的变形观测数据处理方法,使滑坡的预报成为可能.     

高精度大幅面图纸分块扫描拼接技术研究

针对当前大幅面图纸分块扫描拼接中存在的问题,提出一种基于改正扫描仪误差的大幅图纸整体平差的拼接方法.该方法通过平移黑白相间的格网板建立扫描仪的误差模型,同时利用少量的控制点及连接点,然后通过整体平差来直接解求各扫描图像块的几何变换参数.实践证明这种方法具有拼接精度高、速度快以及可不限图幅大小等优点.     

利用坡度差在数字地面模型中过滤数据的实现

介绍一种在DTM中利用坡度差过滤断面数据的新方法,并成功地将该方法应用于程管线断面图自动绘制系统的设计中.     

空间网与地面网联合平差数据处理方法注

针对联合平差数十万个观测值 ,近 2 0万个未知数来说 ,如何有效地组织数据 ,管理数据 ,最大限度地压缩内存是联合平差数据处理的关键。本文主要讨论联合平差数据处理中的主要函数模型和随机模型、大规模稀疏矩阵有效的解算方法并用软件加以实现。作为实例用此软件对小范围的实验区数据进行平差 ,对其解算结果进行了分析     

抗差岭型组合主成分估计及误差影响

本文从有偏估计类中的岭型组合主成分估计出发 ,结合抗差估计理论 ,利用抗差M估计模型 ,提出了一种新的抗差有偏估计法———抗差岭型组合主成分估计。推导了平差参数的抗差岭型组合主成分估计解 ,以及平差参数的验后精度和误差影响函数。计算结果表明 ,抗差岭型组合主成分估计不但能克服法方程系数阵病态性的影响 ,而且能有效地抵制观测值中精差的异常干扰 ,使参数的解更为准确可靠     

抗差卡尔曼滤波及其在动态水准网平差中的应用

介绍了标准卡尔曼滤波方程,总结了稳健M估计的基本方法,并根据等价权原理导出卡尔曼滤波的抗差估计方程,方程的形式与卡尔曼滤波方程相似,给出了卡尔曼滤波稳健估计的计算步骤.最后,以动态水准监测为例进行了模拟计算,证明了该方法的有效性.     

GPS网平差观测量选取的理论分析

由多台GPS接收机在不同时段进行静态观测而组成的观测网形,当采用高精度的科研软件与常用商用软件解算基线时,其基线向量的方差阵不同,前者的方差阵结构是完全的、严密的。同时,在进行GPS网平差时,选取GPS基线的方式及数量的不同,构造的网形也就不同,采用不同的数学模型其得到的平差结果和精度指标也不相同。文章先从理论上进行分析,后用示例进行比较论证。     

Least squares spectral analysis and its application to superconducting gravimeter data analysis

Detection of a periodic signal hidden in noise is the goal of Superconducting Gravimeter (SG) data analysis. Due to spikes, gaps, datum shrifts (offsets) and other disturbances, the traditional FFT method shows inherent limitations. Instead, the least squares spectral analysis (LSSA) has showed itself more suitable than Fourier analysis of gappy, unequally spaced and unequally weighted data series in a variety of applications in geodesy and geophysics. This paper reviews the principle of LSSA and gives a possible strategy for the analysis of time series obtained from the Canadian Superconducting Gravimeter Installation (CGSI), with gaps, offsets, unequal sampling decimation of the data and unequally weighted data points.     

基于测站信息自动构建导线网

为解决导线网条件平差自动组网问题,提出了程序设计的方法和流程,程序依据导线网的野外观测信息自动构造出导线网的拓扑结构,在此基础上提取必要的平差参数和供平差用的观测数据,实现了从观测到平差结果输出全过程的自动化。     

Time-domain identification of dynamic properties of layered soil by using extended Kalman filter and recorded seismic data

A novel time-domain identification technique is developed for the seismic response analysis of soil-structure interaction. A two-degree-of-freedom (2DOF) model with eight lumped parameters is adopted to model the frequency-dependent behavior of soils. For layered soil, the equivalent eight parameters of the 2DOF model arc identified by the extended Kalman filter (EKF) method using recorded seismic data. The polynomial approximations for derivation of state estimators are applied in the EKF procedure. A realistic identification example is given for the layered-soil of a building site in Anchorage, Alaska in the United States. Results of the example demonstrate the feasibility and practicality of the proposed identification technique. The 2DOF soil model and the identification technique can be used for nonlinear response analysis of soil-structure interaction in the time-domain for layered of complex soil conditions. The identified parameters can be stored in a database for use in other similar soil conditions. If a universal database that covers information related to most soil conditions is developed in the future, engineers could conveniently perform time history analyses of soil-structural interaction.