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.     

基于小波变换的单频GPS快速精密定位整周模糊度的解算

对于GPS短基线,载波相位双差观测量已基本消除了卫星轨道误差、钟差、大气折射误差等系统偏差的影响,主要包含距离观测量信息及随机测量误差,其中测量误差是高频的测量噪声,小波变换可将GPS载波相位双差观测量中的观测噪声(高频部分)分解出来。本文利用Coiflets小波基函数对GPS快速定位的原始载波相位双差观测量进行5层分解,通过重构第5层低频系数获得去除噪声的"干净"的载波相位双差观测量,然后利用"干净"的双差观测量进行最小二乘参数估计,以减小测量噪声对GPS快速定位病态方程解的扰动。计算结果表明该方法能够显著提高GPS快速定位中模糊度浮点解的精度,仅利用几个观测历元的数据就可以准确地固定模糊度。     

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。     

基于小波变换的GPS载波相位测量误差分析

多路径效应、接收机电热噪声等个性观测因素是现代GPS双频载波相位差分技术仍然无法克服的GPS测量误差源。利用小波变换，通过多尺度分解筛选的方法，可以将不同误差源的影响从GPS测量结果中有效分离出来，进而达到提高GPS定位精度的目的。     

小波变换在GPS快速定位数据处理中的应用

介绍了小波变换应用于GPS短基线的快速精密定位数据处理方法,分析了将GPS载波相位双差观测量在不同的小波空间和尺度空间进行分解,减小了测量噪声对GPS快速定位中病态方程解的影响,提高了GPS快速定位中基线浮点解的精度.     

地球科学相关论文摘要

04 0 6 0 1　GPS载波相位测量中的信号多路径效应影响研究 袁林果 (西南交通大学 )…∥测绘学报 .- 2 0 0 4 ,33(3) .- 2 10～ 2 16论述了载波相位测量中GPS多路径信号的特征 ,分析了其对载波相位测量的影响 ,提出了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 ,实测数据取得了满意的效果。0 4 0 6 0 2　一个新的GNSS模糊度估计类 P .J .G .Teunissen(荷兰代尔夫特理工大学 )∥武汉大学学报·信息科学版 .-2 0 0 4 ,2 9(9) .- 74 1～ 74 6说明了整数等变估计类较整数估计类和线性无偏估计类的范围大 ,给出了一个…     

基于经验模式分解的滤波去噪法及其在GPS多路径效应中的应用

经验模式分解(Empirical Mode Decomposition,EMD)是一种新的信号处理技术,它是基于数据本身的,且能在空间域中将信号进行分解,从而可以区分噪声和有用信号。根据EMD分解白噪声而得到的本征模式函数(IMF)分量的能量密度与其平均周期的乘积为一常量这一特性,建立一种新的基于EMD滤波去噪方法,并将该方法应用于GPS多路径效应的研究中。通过对模拟数据与GPS实测数据的处理分析,得出以下主要结论:①EMD滤波去噪法与小波方法都能最大限度地削弱测量的随机误差,但EMD滤波去噪法比小波方法更直接,且不受测不准原理及小波函数选择的影响;②相比小波方法,EMD能够更有效地剔除瞬时强噪声,从而能够提取更精确的多路径效应重复性误差改正模型。     

GPS多路径误差滤波方法比较研究

基于GPS多路径时间序列,分别采用Vondrak滤波、经验模式分解(EMD)和小波滤波3种方法构建了GPS多路径误差修正模型,并将其用于削弱多路径效应.通过对模拟数据及实测数据的分析表明,3种方法都能有效地分离不同噪声水平下时间序列中的信号和噪声.同时,利用3种方法构建的多路径修正模型可有效地削弱多路径效应的影响,提高GPS定位精度,但3种方法的优缺点各有不同.     

小波分析在GPS消噪中的应用探讨

采用VB语言与MATLAB语言编程,提取南宁实验GPS控制网观测数据中的原始载波信号,利用小波分析理论在多尺度、多分辨率、可伸缩、可平移等分析方面的优势,分别对提取的原始载波信号、单差观测值、双差观测值采用bd3小波函数进行3层小波分解,研究高频信号特点以及不同差分方法消除噪声的效果。将小波分析理论作为数学工具,实施GPS观测数据小波分解和重组,对于发现并削弱GPS误差具有一定的参考价值。     

小波去噪在GPS监测数据处理中的应用研究

在GPS观测的数据中,往往存在大量的噪声,噪声的存在对卫星信号造成了一定程度的干扰。利用小波去噪的方法可以分解GPS载波信号,得到信号的高频和低频不同的频率成分,从而有效的剔除GPS信号的噪声,调高GPS变形监测数据的精度。     

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.     

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。     

双极性天线在多路径效应探测中的应用

多路径效应是影响卫星定位精度和稳定性的重要因素。针对多路径环境复杂多变难以进行分析的问题,该文提出了一种利用双极性天线探测多路径的方法。详细介绍了反射信号的极性特征;通过判断信号的极性可以有效地区分直射信号和反射信号。分析了通过信号极性实现多路径探测的理论:组成双极性天线的右螺旋圆极化天线和左螺旋圆极化天线能够分别输出卫星信号中的右螺旋圆极化分量和左螺旋圆极化分量,如果两个分量的载噪比差值大于一定的门槛值,就可以推断卫星信号在传输过程中经历了多路径效应。最后通过仿真实验验证了该方法的可行性和有效性。     

Wavelet packets based denoising method for measurement domain repeat-time multipath filtering in GPS static high-precision positioning

Repeatable satellite orbits can be used for multipath mitigation in GPS-based deformation monitoring and other high-precision GPS applications that involve continuous observation with static antennas. Multipath signals at a static station repeat when the GPS constellation repeats given the same site environment. Repeat-time multipath filtering techniques need noise reduction methods to remove the white noise in carrier phase measurement residuals in order to retrieve the carrier phase multipath corrections for the next day. We propose a generic and robust three-level wavelet packets based denoising method for repeat-time-based carrier phase multipath filtering in relative positioning; the method does not need tuning to work with different data sets. The proposed denoising method is tested rigorously and compared with two other denoising methods. Three rooftop data sets collected at the University of Nottingham Ningbo China and two data sets collected at three Southern California Integrated GPS Network high-rate stations are used in the performance assessment. Test results of the wavelet packets denoising method are compared with the results of the resistor–capacitor (RC) low-pass filter and the single-level discrete wavelet transform (DWT) denoising method. Multipath mitigation efficiency in carrier phase measurement domain is shown by spectrum analysis of two selected satellites in two data sets. The positioning performance of the repeat-time-based multipath filtering techniques is assessed. The results show that the performance of the three noise reduction techniques is about 1–46 % improvement on positioning accuracy when compared with no multipath filtering. The statistical results show that the wavelet packets based denoising method is always better than the RC filter by 2–4 %, and better than the DWT method by 6–15 %. These results suggest that the proposed wavelet packets based denoising method is better than both the DWT method and the relatively simple RC low-pass filter for noise reduction in multipath filtering. However, the wavelet packets based denoising method is not significantly better than the RC filter.     

桥梁GNSS-RTK变形监测数据的多滤波联合去噪处理

针对桥梁GNSS-RTK变形监测中多路径效应和随机噪声的影响，提出了一种基于Chebyshev滤波和自适应噪声的完备集合经验模态分解（CEEMDAN），以及小波阈值（WT）降噪技术的多滤波联合降噪方法。该方法首先对监测信号实施Chebyshev滤波抑制多路径效应；然后进行CEEMDAN分解，基于自相关性分析，对噪声IMF分量进行WT降噪去除随机噪声。本文以天津海河大桥GNSS-RTK变形监测作为试验，对监测数据进行多滤波降噪处理。结果表明：本文所提的多滤波降噪方法能有效抑制多路径效应和随机噪声，GNSS-RTK与多滤波降噪相结合的方法能够准确识别桥梁真实动态位移，为桥梁GNSS-RTK监测数据降噪处理提供了一种良好的途径。     

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。     

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.     

CVVF方法用于GPS多路径效应的研究

将交叉证认法与Vondrak数字滤波器相组合,提出一种分离测量资料中信号与噪声的新方法,即CVVF方法,并将该方法用于GPS多路径效应的研究中.对数字模拟试验和实际观测资料的分析表明,该方法能最大限度地削弱测量的随机误差,使资料序列中的信号和噪声合理分离.同时,利用GPS多路径效应周期性重复的特性,可有效地削弱多路径效应对观测结果的影响,从而提高GPS定位精度.     

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.