奇异谱分析滤波法在消除GPS多路径中的应用

基于奇异谱分析(singularspectrumanalysis,SSA)的基本思想,利用噪声与信号的赫斯特(Hurst)指数有显著差异这一特性,提出了一种新的SSA滤波法,同时给定了嵌入维数犔与重构阶次犘的确定标准,并将该方法应用于GPS多路径的研究中。通过模拟数据及实测GPS坐标序列的数据分析,结果表明SSA滤波法是一种有效的去噪方法,其去噪效果与小波滤波与经验模态分解(empriricalmodedecomposition,EMD)滤波相当。针对多路径效应周日重复性的特点,利用该滤波方法建立改正模型,可有效地削弱多路径效应的影响,进而提高GPS动态变形监测的精度。     

基于小波变换的GPS动态变形分析

介绍了小波滤波去噪的原理并讨论在动态环境下GPS多路径效应的重复性问题。首先利用小波方法对静态观测数据的残差进行去噪,提取具有系统性的多路径误差改正模型。然后,根据多路径误差重复性的特点,对后续动态观测的数据进行改正。通过实验证明:经重复性模型改正后残余的多路径噪声符合正态分布的特点。然后采用小波软阈值去噪方法,消除剩余的多路径误差,可进一步提高动态变形监测的精度。     

基于交叉证认的EMD滤波及其在GPS多路径效应中的应用

利用交叉证认的方法,提出一种新的基于EMD滤波去噪方法,并将其应用于GPS多路径效应的研究中。通过模拟实验及实测数据分析表明,该方法能够自适应地选择IMF中的信号层数,削弱随机噪声,合理地分离信号和噪声。利用该滤波方法去噪并建立具有重复性的多路径误差效应改正模型,可有效地削弱多路径效应的影响,进而提高GPS动态变形监测的精度。     

GPS载波相位测量中的信号多路径效应影响研究

当利用GPS进行高精度变形监测时,GPS信号的多路径效应成为影响GPS变形监测精度和可靠性的一种不可忽略的误差源.本文针对GPS载波相位测量中的多路径效应影响进行理论和试验分析.论述载波相位测量中GPS多路径信号的特征,分析它对载波相位测量的影响,提出在坐标域用移动平均进行短基线静态GPS测量多路径误差探测的方法.通过实测数据进行分析,取得满意的效果.     

动态变形监测多路径实时修正模型研究

多路径效应是GPS高精度实时动态变形监测中的主要误差源,通过经验模态分解方法对三维坐标序列进行多尺度分解和重构,提取作为趋势项的多路径模型;并利用多路径效应的周日强相关性特点,对第二天动态坐标进行多路径效应去除,得到削弱多路径效应后的坐标序列。研究结果表明,多路径效应削弱后的坐标序列稳定性明显增强,坐标的精度明显提高。     

GPS结构变形监测中的多路径效应研究

GPS技术已在各种结构工程的变形监测中得到广泛应用,但多路径效应的影响是目前限制GPS定位精度和可靠性进一步提高的瓶颈.本文通过对多路径效应特点的分析和各种多路径效应削减方法的讨论,对结构体变形监测中的多路径效应削减方法进行了系统研究,使GPS定位技术能满足结构工程安全监测的精度要求.论文的主要研究内容和结论如下:     

GPS多路径效应中的EEMD时空滤波器

根据结构动态监测中GPS多路径效应的日重复性和低频周期等特性,本文研究了一种基于集成经验模态分解(EEMD)技术的滤波方法,构造了EEMD时空滤波器。通过计算连续两天GPS动态监测数据EEMD的相关系数,提取GPS监测数据中的多路径效应。实验结果表明了该方法的有效性,为结构动态变形模态分析提供了有效数据。     

GPS多路径误差分析及探测方法

多路径误差严重影响动态GPS测量精度,且很难将其彻底消除.介绍多路径效应的机理及特性,利用相同环境下、连续卫星周期间数据取差以及连续历元坐标序列的移动平均方法削弱多路径误差,提高定位精度.     

北斗卫星导航系统在地理国情监测中的应用

介绍了北斗卫星导航系统的发展和地理国情监测中的基本情况。通过北斗卫星导航系统单点定位解算验证系统精度。分析了卫星数量、PDOP值、多路径效应、位置精度和速度精度,表明北斗卫星导航系统和GPS系统的定位精度相当。     

GPS多路径效应实验测试与分析研究

作为影响GPS测量信号的干扰源,多路径效应为众多研究者所关注。多路径效应使得GPS测量的精度降低,严重时还将引起信号失锁。针对这一问题,文中从多路径效应产生的原理出发,设计并实施无线电干扰和镜面反射干扰实验,分析多路径效应对GPS单点定位精度、基线长度精度和网精度的影响。在既有的研究成果基础上,提出随着距离的变化多路径效应的影响程度不同、对网精度影响最小、对单点定位精度影响最大等结论,并总结了减弱多路径效应的相关措施。     

Characteristics of multipath effects in GPS dynamic deformation monitoring

IntroductionThere are many factors that affect the precisionand reliability of GPS measuring. Generally, theerror sources can be grouped into the followingthree classes: errors correlated with the satellites(such as ephemeris error, satellite clock error,…     

Multipath mitigation via component analysis methods for GPS dynamic deformation monitoring

Multipath is one of the main error sources in high-precision global positioning system (GPS) dynamic deformation monitoring, as it is difficult to be mitigated by differencing between observations. In addition, since a specific frequency threshold value between multipath and deformation signals may not exist, multipath is usually inseparable from the low-frequency vibration signal using conventional frequency-domain filter methods. However, the multipath repeats in two sidereal days when the surroundings of a GPS antenna remain unchanged. This characteristic can be exploited to model and thus mitigate multipath effectively in dynamic deformation monitoring. Unfortunately, a major issue is that the degree of repeatability decreases as the interval between first day and subsequent days increases. To overcome this problem, we develop a new sidereal filtering referred to as reference EMD-ICA (EMD-ICA-R), where empirical mode decomposition (EMD) and independent component analysis (ICA) are jointly used to model multipath and renew the reference multipath. For the successful implementation of the EMD-ICA-R, an a priori denoised multipath signal is needed as a reference. We further propose to use the principal component analysis (PCA) method to extract more accurate reference multipath signal and form a combined PCA-EMD-ICA-R approach. Simulation experiments with a motion simulation platform were conducted, and the testing results indicate that the proposed methods can mitigate the multipath by around 67 % when a reliable reference multipath signal is extracted from a static situation. Furthermore, simulation experiments with different deformation signals added into the coordinate time series of three consecutive days show that the two proposed methods are also effective in a dynamic situation. Since wavelet filtering is used to denoise the reference multipath signals in the new approaches, simulation experiments with several wavelet filters are tested, and the results indicate that the PCA-EMD-ICA-R approach can work well with various wavelet filters.     

单历元GPS变形监测数据处理方法的研究

讨论了变形监测中ＧＰＳ单历元观测数据处理方法,重点是模糊度搜索空间的构成和搜索,最优解的获得和检验以及利用相位和伪距观测量提取多路径的影响。分析了所提方法的测试结果和处理快速变形所能达到的精度。     

GPS多路径重复性试验研究

信号衍射和多路径效应是限制GPS定位精度进一步提高的瓶颈,观测中两者往往同时存在。衍射效应具有不完全重复的特性,为了研究多路径重复性并使其不受信号衍射的影响,本文提出先应用SIGMA-Δ信噪比加权模型削弱信号衍射的影响,再运用改进恒星时滤波法分析多路径重复性。实验观测资料分析表明,SIGMA-Δ模型能有效削弱衍射信号对定位结果影响,并且保留主要的多路径信号;而改进恒星时滤波法能适应测站周围多路径环境的变化,从而最大限度地削减多路径误差。两者组合比传统的恒星时滤波更能有效提高GPS的动态定位精度。     

Filtering GPS time-series using a Vondrak filter and cross-validation

Multipath disturbance is one of the most important error sources in high-accuracy global positioning system (GPS) positioning and navigation. A new data filtering method, based on the Vondrak filter and the technique of cross-validation, is developed for separating signals from noise in data series, and applied to mitigate GPS multipath effects in applications such as deformation monitoring. Both simulated data series and real GPS observations are used to test the proposed method. It is shown that the method can be used to successfully separate signals from noise at different noise levels, and for varying signal frequencies as long as the noise level is lower than the magnitude of the signals. A multipath model can be derived, based on the current-day GPS observations, with the proposed method and used to remove multipath errors in subsequent days of GPS observations when taking advantage of the sidereal day-to-day repeating characteristics of GPS multipath signals. Tests have shown that the reduction in the root mean square (RMS) values of the GPS errors ranges from 20% to 40% when the method is applied.     

一种基于交叉证认技术的自适应小波变换及其在削减GPS多路径误差中的应用

多路径效应影响是目前限制GPS定位精度进一步提高的瓶颈。提出用交叉证认技术自动识别小波分解的信号层,再通过小波重构实现降噪和信号提取,并将该方法应用于GPS多路径误差的削减中。对模拟数据和实际GPS观测资料的分析表明,该方法能合理分离不同噪声水平下资料序列中的信号和噪声;当噪声水平小于信号振幅的一半时,能成功分离资料序列中的高频信号。同时,运用该方法得到的多路径改正模型和GPS多路径效应的重复性,可有效地削弱多路径效应的影响,提高GPS定位精度。