基于高程异常拟合二次多项式模型的矿山测量数据处理方法研究

Research on mine measurement data processing based on quadratic polynomial model of elevation anomaly fitting

针对矿山测量数据存在精度差、易受外界因素干扰、测绘难以维持且基准不统一等问题,采用高程异常拟合二次多项式模型,推导出了模型显著性检验的算法与方法以及随机模型误差对函数模型显著性检验的影响;通过对Reilly线性化函数的使用,实现了应用模型拟合残差对未知点随机信息的推估;并且使用残差推估方程与Reilly函数,计算了高程异常拟合后残差推估,矿区高程异常拟合实现证明,利用协方差函数推估高程异常拟合残差的可行性与有效性,研究为解决矿山测量数据存在的问题提供一定理论依据。

In allusion to the problems that the measurement data of mine have poor accuracy, easily disturbed by external factors, diffi- cult to maintain the survey and the benchmark is not uniform, this paper adopted quadratic polynomial model fitting height anomaly to deduce the algorithm and method of model significance test and stochastic model error. On the basis of the Reilly linearization function, the application model was fitted to the random information of the unknown points of the residual estimation;and the residual error esti- mation equation and the Reilly function are used to calculate the height abnormality fitting residual estimation, and mining area abnormal fitting proved that the use of covariance function to estimate the feasibility and validity of elevation abnormal fitting residuals, to provide some theoretical basis for solving the existing problems of mine measurement data.