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。     

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。     

多频组合数据在原始载波观测值预处理中的应用

周跳及粗差的产生将破坏GPS原始载波观测数据的连贯性,而传统的探测修复方法由于受到采样间隔的影响,不能完全对大采样率条件下原始观测数据周跳进行修复及较小粗差探测。随着GPS现代化中3个频率的应用,将多频组合观测值中好的特性应用到周跳及粗差的探测与修复已成为可能。通过多频载波相位组合观测值的波长特性,结合传统的伪距/载波探测原理,利用模拟的GPS多频数据进行各种情况下周跳与粗差的探测及修复,同时对一条GPS基线进行原始观测数据预处理作实例分析。结果表明,通过多频数据组合能够完全实时修复大采样率条件下各种情况的周跳,可以实时探测出0.2周以上的粗差。     

基于GPS相位观测值差分的小波变换在周跳探测中的应用

针对GPS载波相位观测值中出现的周跳,首先分别对GPS相位观测值做单差和双差处理,再根据小波变换检测信号的奇异性原理,将GPS相位观测值发生周跳处视为信号的奇异点,通过MATLAB编程,分别对相位单差和双差观测值进行小波变换来探测周跳.实验证明,基于差分法的小波变换周跳探测效率比较高,周跳位置探测比较准,而且双差观测值的周跳探测比单差观测值效果好.     

基于小波的GPS基线解算精化处理技术及其应用

采用小波技术对GPS信号进行处理,提出基于小波变换的周跳与粗差的探测.利用基于小波变换的小波滤波法对于提高GPS双差相位观测值的信噪比具有较好的效果,对其相位观测值进行小波滤波,消除或削弱多路径效应和各种观测噪声,使其观测值得以净化.这种方法对于缩小模糊度搜索空间及提高模糊度解的有效性有明显的作用,从而提高基线解算的精度.     

基于小波分析的GPS双差观测数据消噪方法研究

通过双差方法难以消除的多路径误差、接收机观测噪声等非模型化误差会大大影响GPS动态定位的精度.基于小波分析的理论,对GPS双差观测数据序列的消噪问题进行研究,结果表明,利用小波去噪原理,可有效地从受到强噪声干扰的GPS观测数据序列中提取变形特征信息,增强基线解算的有效性,提高GPS定位精度,解决传统技术对GPS动态监测...     

小波分析在单频GPS快速精密定位中的应用研究

单频GPS快速定位方程是严重病态的,应用最小二乘原理得到的模糊度浮点解大大偏离其准确值,应用LAMBDA方法难以正确地固定模糊度。本文将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和重构,去除高频测量噪声,可减小测量噪声对GPS快速定位中病态方程解的影响,提高模糊度浮点解的精度,缩小模糊度搜索空间。实验表明,对于GPS短基线,仅利用1min左右的单频载波观测数据,经过基于haar、db4、coif4和sym4小波的5尺度小波变换后,可获得较准确的模糊度浮点解,应用LAMBDA法可正确地固定模糊度,达到厘米级定位精度。     

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。     

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.     

有色噪声观测量的逐次静态滤波与配置

通过改化观测方程,将有色噪声观测值转化为白噪声的虚拟观测值,用白噪声逐次滤波公式进行滤波计算.有色噪声观测值的逐次静态滤波理论可用于GPS数据处理.GPS载波相位观测值经过测站间、卫星间、历元间的3次差分计算,消除了大部分误差和整周模糊度,并使周跳成为孤值,但是相邻历元间隔的三差观测值误差相关造成其协方差阵呈现出分块三对角阵,使所求矩阵占据的时间和内存太大.利用有色噪声观测值的逐次静态滤波的理论,可消去相关性,减少计算时间和内存.这种顾及三差观测值的相关性的算法是严密的.     

TJS-2 geostationary satellite orbit determination using onboard GPS measurements

This study analyzes the quality of onboard data of tracking signals from GPS satellites on the far side of the earth and determines the orbit of the geostationary satellite using code and carrier phase observations with 30-h and 3-day orbit arc length. According to the analysis results, the onboard receiver can track 6–8 GPS satellites, and the minimum and maximum carrier to noise spectral densities were 24 and 45 dB-Hz, respectively. For a GPS receiver on a high-altitude platform above the navigation constellations, the blocking of the earth and a weak signal strength usually cause a piece-wise GPS signal tracking and an increase in the number of ambiguity parameters. Individual GPS satellites may be continuously tracked for as little as several minutes and as long as 3 h. Moreover, considering the negative sign of elevation angles reflects the fact that GPS satellites are tracked below the receiver in the study. GPS satellites appear mainly in the elevation angle range of ??53° to ??83°, and dilution of precision values could reach ten or one hundred and more. Also, it is observed that when a signal suffers from atmospheric refraction, other GPS signals tracked simultaneously by the receiver experience strong systematic errors in the code observations. Based on single-frequency code and carrier phase measurements, the mean 3D root mean square (RMS) value of the overlap comparisons between 30-h orbit determination arcs is 2.14 m. However, we found that there were also some biases in the carrier phase residuals, which contributed to poor orbit accuracy. To eliminate the effects of the biases, we established a correction sequence for each GPS satellite. After corrections, the mean 3D RMS was reduced to 0.99 m, representing a 53% improvement.     

小波包分析在GPS振动观测中的应用

将小波包分析应用于GPS振动观测数据处理,研究小波包分析在异常值探测、信号特征提取、去噪中的应用。首先对信号分解和单支重构,验证小波包分析探测异常值的能力。针对小波包分析含有丰富的高频信息,采用奇异谱分析方法提取高频部分的振幅和频率。小波包分析的去噪能力优于小波分析。     

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.     

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。     

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.     

A new method to mitigate multipath error in single-frequency GPS receiver with wavelet transform

One of the major errors in high-precision GPS positioning is multipath. Multipath effect modeling and reduction have been a challenging issue in high-accuracy GPS positioning applications due to its special properties. Different methods have been employed to mitigate this error including hardware and software approaches. We reduce C/A code multipath error by adopting an efficient software method which uses wavelet transform as a basic data processing trend. The key idea of the proposed method is using stationary wavelet transform (SWT) in GPS signal data processing. Since we have used SWT, there is complete access to high-frequency and low-frequency terms in both time and frequency domains, and we can apply appropriated procedures to mitigate this error. The multipath error mostly is a low-frequency term. In our proposed method, the double difference (DD) residuals are applied to the SWT to identify the multipath disturbance. The extracted multipath is then used to correct DD observations. Our experiments include three data sets to investigate the proposed method and compare it with existing algorithms. We used simulations for two of these data sets. The results indicate the efficiency of the proposed method over existing algorithms.     

一种低动态高抖动环境下的GPS/INS紧组合方法

针对低动态高抖动环境下,影响GPS/INS紧组合精度的重要因素——惯性测量单元(IMU)数据中的噪声,该文提出利用小波降噪方法分离IMU数据中的噪声和有用信号以提高GPS/INS紧组合的精度。首先对IMU数据进行小波分解后得到的高频系数进行阈值量化处理,然后将GPS观测数据与降噪后的IMU数据进行GPS/INS紧组合解算,最终得到载体的导航信息。实例结果表明,该方法可以大幅提升GPS/INS紧组合的精度和稳定可靠性。