GPS动态监测中多路径效应的规律性研究

在分析GPS多路径效应特性的基础上,结合GPS动态变形监测的特点,对连续多天的观测数据解算结果采用滤波与周日位置求差相结合的方法进行数据处理。研究结果表明,多路径误差具有较强的周日重复性,在有效地削弱多路径效应的影响后,GPS动态监测的三维位置精度可以达到mm级,尤其是垂直方向的精度改善明显。     

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.     

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.     

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。     

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。     

Pseudo-Satellite Applications in Deformation Monitoring

In this article, three general classes of potential pseudolite applications for deformation monitoring are described. The first is GPS augmentation with pseudolite(s), which is suitable for circumstances such as urban canyons, or for monitoring in valleys and deep open-cut mines. The second is indoor applications of pseudolite deformation monitoring systems. Pseudolite arrays can, in principle, completely replace the GPS satellite constellation. This could extend the “satellite-based” deformation monitoring applications into tunnels or underground, where GPS satellite signals cannot be tracked. The last case is an inverted pseudolite-based deformation monitoring system, where a “constellation” of GPS receivers with precisely known “orbits” track a mobile pseudolite. The system consists of an array of GPS receivers, the base reference pseudolite, the mobile pseudolite, and a central processing system. However, in the case of such pseudolite-only or hybrid pseudolite-GPS deformation monitoring systems, some additional issues need to be addressed. These include multipath, atmospheric delay effects, and pseudolite location-dependent biases. To address deformation monitoring applications, some practical procedures to mitigate or eliminate their influence are suggested. Some experiments were carried out using NovAtel GPS receivers and IntegriNautics IN200CXL pseudolite instruments. The experimental results indicate that the accuracy of the height component can indeed be significantly improved – the RMS of the vertical component has been reduced by a factor of 4, to the same level as the horizontal components. Their performance will be demonstrated through case study example. ? 2002 Wiley Periodicals, Inc.     

GPS动态监测试验与精度分析

由于GPS定位精度的不断提高,其在工程变形监测中得到了越来越广泛的应用。结合一次动态监测实验,客观评价了GPS的精度,本文介绍了该试验的实施方案及监测结果,并通过大量实验数据统计分析了此次GPS动态监测的精度,取得了不错的效果。试验证明,GPS动态监测能够满足工程应用的需要。     

伪卫星增强GPS方法在变形监测中的应用研究

应用GPS对深开采的露天矿以及深山峡谷中的水库大坝进行变形监测,由于接收到的GPS卫星数目减少,导致GPS定位精度大大降低。采用伪卫星增强GPS的定位技术是解决这个问题的有效途径之一。提出GPS伪卫星组合测量新方法,建立组合观测量模型,开发减小伪卫星多路径效应的方法。基于实际的水电站观测数据分析伪卫星增强GPS提高定位精度的效果,给出GPS伪卫星组合定位的试验结果并验证所开发方法的有效性。     

伪卫星多路径效应分形特征及其削弱方法研究

多路径效应是伪卫星应用在精密定位领域的一项主要误差源,本文从验证多路径效应分形特征入手,利用小波分析在研究分形及信号去噪方面的优势,研究了分形信号与高斯白噪声的模极大值在小波变换下表征的不同特点,针对静态环境下伪卫星的应用,提出一种基于分形理论的多路径误差的消除方法。通过设计试验进行精度分析,验证了本文方法的有效性,且该算法从信号自身的分形特征入手,不需要额外的先验信息,对环境等条件要求较低,比较适合在形变监测等静态环境下应用。     

桥面复杂环境下BDS／GPS数据质量监测与分析

分别阐述了BDS／GPS多路径效应的产生机理以及相应的消除和削弱措施,利用统计分析方法对桥梁变形监测过程中复杂环境下监测点的BDS／GPS的多路径效应进行对比分析,以及分析BDS、GPS多路径误差与桥梁桥塔、缆索、车流量等影响因素的关系。实测数据结果表明,GPS的多路径效应值相比于BDS的GEO卫星较大,与IGSO卫星基本相同,优于MEO卫星;多路径误差与卫星高度角呈负相关关系;桥梁桥塔、缆索、车流量是影响多路径效应的重要因素。      

Multipath Mitigation of Continuous GPS Measurements Using an Adaptive Filter

Though state-of-the-art dual-frequency receivers are employed in the continuous Global Positioning System (CGPS) arrays, the CGPS coordinate time series are typically very noisy due to the effects of atmospheric biases, multipath, receiver noise, and so on, with multipath generally being considered the major noise contributor. An adaptive finite-duration impulse response filter, based on a least-mean-square algorithm, has been developed to derive a relatively noise-free time series from the CGPS results. Furthermore, this algorithm is suitable for real-time applications. Numerical simulation studies indicate that the adaptive filters is a powerful signal decomposer, which can significantly mitigate multipath effects. By applying the filter to both pseudorange and carrier phase multipath sequences derived from some experimental GPS data, multipath models have been reliably derived. It is found that the best multipath mitigation strategy is forward filtering using data on two adjacent days, which reduces the standard deviations of the pseudorange multipath time series to about one fourth its magnitude before correction and to about half in the case of carrier phase. The filter has been successfully applied to the pseudorange multipath sequences derived from CGPS data. The benefit of this techniques is that the affected observable sequences can be corrected, and then these corrected observables can be used to improve the quality of the GPS coordinate results. ? 2000 John Wiley & Sons, Inc.     

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。     

BDS精密单点定位在桥梁变形监测中的应用

桥梁变形监测是进行桥梁健康评估和后期修缮的重要内容．本文基于北斗卫星导航系统（BDS）精密单点定位技术,对实时采集的高频率BDS／GPS数据进行精密单点定位(PPP)静态和动态处理,并以相对静态定位结果作为参考,分析在桥梁复杂环境下BDS的PPP的精度,并把北斗动态PPP结果与GPS做对比．研究结果表明,在1 h连续变形监测时间左右,北斗静态PPP精度和BDS动态PPP定位精度可以达到厘米级,可以监测出大型车辆经过桥梁时的变形情况,并与GPS监测变形趋势基本一致．      

主成分分析模型及在变形监测中的应用

随机误差和多径效应作为GPS变形监测中的主要误差源,严重影响着GPS测量精度。针对这一问题,本文将主成分分析(Principal Component Analysis,PCA)模型引入GPS变形监测领域,首先利用传统PCA方法将测量数据转换至特征空间,通过剔除小特征值对应的特征向量实现对高斯分布随机噪声的抑制,然后将多径噪声作为色噪声进行分析,提出一种广义PCA方法利用多径噪声的时间相关性对其进行滤除,基于实际工程测试数据的实验结果表明,相对于传统的小波噪声抑制方法,所提方法可以获得更好的噪声抑制性能。     

Adaptive wavelet transform based on cross-validation method and its application to GPS multipath mitigation

Global positioning system (GPS) multipath disturbance is a bottleneck problem that limits the accuracy of precise GPS positioning applications. A method based on the technique of cross-validation for automatically identifying wavelet signal layers is developed and used for separating noise from signals in data series, and applied to mitigate GPS multipath effects. Experiments with both simulated data series and real GPS observations show that the method is a powerful signal decomposer, which can successfully separate noise from signals as long as the noise level is lower than about half of the magnitude of the signals. A multipath correction model is derived based on the proposed method and the sidereal day-to-day repeating property of GPS multipath signals to remove multipath effects on GPS observations and to improve the quality of the GPS measurements.