黄声享, 刘经南. GPS监测系统基准形变分析与动态随机模拟[J]. 武汉大学学报 ( 信息科学版), 2000, 25(6): 485-490.
引用本文: 黄声享, 刘经南. GPS监测系统基准形变分析与动态随机模拟[J]. 武汉大学学报 ( 信息科学版), 2000, 25(6): 485-490.
HUANG Shengxiang, LIU Jingnan. Datum Deformation Analysis and Dynamic Stochastic Simulation for GPS Monitoring System[J]. Geomatics and Information Science of Wuhan University, 2000, 25(6): 485-490.
Citation: HUANG Shengxiang, LIU Jingnan. Datum Deformation Analysis and Dynamic Stochastic Simulation for GPS Monitoring System[J]. Geomatics and Information Science of Wuhan University, 2000, 25(6): 485-490.

GPS监测系统基准形变分析与动态随机模拟

Datum Deformation Analysis and Dynamic Stochastic Simulation for GPS Monitoring System

  • 摘要: 把GPS自动化监测系统中工作基点的长期观测资料看成为与时间有关的动态随机序列,应用随机过程理论的相关分析法和数字信号系统中的频谱分析法,研究了隔河岩大坝GPS自动监测系统中工作基点的稳定性。结果表明,该系统的工作基点在垂直方向上存在微小线性形变,并有约1a的长周期变化趋势特征。为验证分析结论的可靠性,采用了随机数生成器进行随机数序列仿真,所得结果是一致的。研究表明,用大子样容量的时序观测资料可以识别隐含在时序误差中的微小形变趋势分量。

     

    Abstract: It is a very important work to analyze the working datum marks' stability for GPS deformation monitoring system.After the system working some period of time,a large amount of deformation observation data can be obtained,and these data can be described as one time series.If the datum marks is steady-going during this period of time,the time series of the observed data should be an ergodic stochastic series and cohere with the condition and nature of a stationary stochastic process. The autocorrelation function is one of eigenvalues of the stochastic process,it reflects the relativity of observations in different time.If the stochastic functions are not correlative,the estimation of their standard autocorrelation function should tend to zero when the time tends to infinity.Hereby,we can identify whether the studied time series is ergodic or not.In addition,if the stationary stochastic process contains periodical components,its autocorrelation function has periodical components as well,and the periodicity of both is same. FK(W20。40ZQ Generally speaking,the observed data of GPS deformation monitoring system is very difficult to be equally spaced,occasionally missing data within quite a length time,by reason of the influence of various factors (subjective and objective).The frequency spectral analysis is a quite efficient method to analyze periodical signals,but its prominent limitation is that the data must be equally spaced.For this reason,in this paper the spectral analysis is only applied to identify whether the time series has periodical components or not.If it contains periodical components,a higher order polynomial is used to approach the data series by the leasts-quares method.The practice testifies that this method is grealy effective which is applied for describing the long periodical alteration of the time series. Taking GPS automatic monitoring system of outside deformation for Geheyan dam on the Qingjiang river as example,this paper analyzes the deformation characteristics of tow working datum marks for this system.Results show that in vertical component,there is a small linear displacement trend with yearly 1.64mm,and a long periodical deformation trend with about one year;in horizontal directin,the linear displacement trend is not distinct,but there are also the deformation characteristics of a long periodical trend.In order to test and verify above results,the random data generator is employed to simulate the random data series,the end results are coincident.The research indicates that the small linear displacement trend included in the time series'errors can be identified by the time series' data of large sample quantity.

     

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