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。     

GPS多路径效应实例计算与分析

本文讨论了一个GPS伪距多路径值计算及其频谱分析的方法。文中首先介绍了GPS多路径试验测量和观测数据采集的程序。然后探测和修复周跳、再利用伪距多路径计算公式,获得GPS测量中的伪距多路径值。实例证明该方法有效地计算出了伪距多路径值。     

GPS multipath mitigation: a nonlinear regression approach

Under the assumption that the surrounding environment remains unchanged, multipath contamination of GPS measurements can be formulated as a function of the sidereal repeatable geometry of the satellite with respect to the fixed receiver. Hence, multipath error estimation amounts to a regression problem. We present a method for estimating code multipath error of GPS ground fixed stations. By formulating the multipath estimation as a regression problem, we construct a nonlinear continuous model for estimating multipath error based on well-known sparse kernel regression, for example, support vector regression. We will empirically show that the proposed method achieves state-of-the-art performance on code multipath mitigation with 79 % reduction on average in terms of standard deviation of multipath error. Furthermore, by simulation, we will also show that the method is robust to other coexisting signals of phenomena, such as seismic signals.     

GPS码跟踪环自适应多径消除算法

根据多径信号的产生机理,在对GPS接收机中的码跟踪环多径信号模型研究的基础上,提出了采用自适应滤波的来消除GPS多径效应的算法。自适应滤波的方法不需要估计模型的系统参数,而直接通过自适应滤波将多径信号滤除。在有噪声的情况下,自适应滤波的RLS算法是最小二乘意义下的最优估计,仿真的结果表明采用自适应滤波算法可以快速的消除多径的影响,修正鉴相函数的过零点偏差,提高码跟踪环的跟踪精度。由于自适应滤波算法是递推算法,易于软、硬件实现。     

GPS测站多路径效应建模研究

GPS伪距观测量由于不存在周跳和整周模糊度的问题,可用来实现动态导航定位,但受到多路径效应影响较为严重,定位精度较低。本文以BJFS站为例,计算了伪距多路径效应,首次大量采用单历元数据,以球谐函数的形式建立了伪距多路径效应、高度角和方位角间的函数模型。建模过程中用截断奇异值分解方法解决了单历元数据引起的的病态问题,求得了模型的最小二乘解。在伪距观测数据中加入模型计算的伪距多路径效应改正,用Bernese软件的动态单点定位功能进行伪距单点定位。对BJFS站的伪距动态定位结果进行统计分析,结果表明单点定位精度得到了改善。     

一种改进扩展卡尔曼滤波算法的GPS多径抑制应用

在用EKF算法消除微弱GPS卫星信号中的噪声,并估计出多径幅度与码相位时延的码跟踪环中,由于各种误差的存在,从而降低了环路的跟踪性能。针对这一问题,该文在EKF算法的基础上提出了一种LSEKF算法,该LSEKF算法用最小二乘估计的原理对EKF算法所用的采样观测点进行修正,构造出一组无偏、均方误差和最小与空间分布确定的新型采样观测点,用来进行后续的滤波估计。仿真结果表明,相比EKF算法,LSEKF算法拥有更高的伪码跟踪精度,而且收敛速度更快,跟踪门限也更低。     

Forward modeling of GPS multipath for near-surface reflectometry and positioning applications

Multipath is detrimental for both GPS positioning and timing applications. However, the benefits of GPS multipath for reflectometry have become increasingly clear for soil moisture, snow depth, and vegetation growth monitoring. Most multipath forward models focus on the code modulation, adopting arbitrary values for the reflection power, phase, and delay, or they calculate the reflection delay based on a given geometry and keep reflection power empirically defined. Here, a fully polarimetric forward model is presented, accounting for right- and left-handed circularly polarized components of the GPS broadcast signal and of the antenna and surface responses as well. Starting from the fundamental direct and reflected voltages, we have defined the interferometric and error voltages, which are of more interest in reflectometry and positioning applications. We examined the effect of varying coherence on signal-to-noise ratio, carrier phase, and code pseudorange observables. The main features of the forward model are subsequently illustrated as they relate to the broadcast signal, reflector height, random surface roughness, surface material, antenna pattern, and antenna orientation. We demonstrated how the antenna orientation—upright, tipped, or upside-down—involves a number of trade-offs regarding the neglect of the antenna gain pattern, the minimization of CDMA self-interference, and the maximization of the number of satellites visible. The forward model was also used to understand the multipath signature in GPS positioning applications. For example, we have shown how geodetic GPS antennas offer little impediment for the intake of near-grazing reflections off natural surfaces, in contrast to off metal, because of the lack of diversity with respect to the direct signal—small interferometric delay and Doppler, same sense of polarization, and similar direction of arrival.     

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.     

GPS多路径误差处理技术

GPS高精度定位和授时中存在多路径效应。本文介绍了多路径效应产生的原理、作用特性,并着重从三个方面归纳、分析比较了目前国内多种关于多路径误差的处理技术。本文在北京基站进行了GPS单站定时实验,分析实验结果认为,多路径效应是GPS授时中不可忽视的误差因素。     

Variable length LMS adaptive filter for carrier phase multipath mitigation

Multipath on carrier phase measurements is among the major error sources for short baseline positioning. A new method is proposed to improve the accuracy of the positioning results by mitigating the multipath effects on carrier phase measurements using the variable length Least Mean Square (VLLMS) adaptive filter. The performance of the filter is analyzed as well as compared with that of the standard LMS adaptive filter using a set of carrier phase observation data of two consecutive days collected in a short baseline experiment. Because the two antennas are static, the multipath error is the only dominant component in the carrier phase double-differenced residuals and indicates a repeated pattern. The numerical results show that both filters can significantly mitigate the multipath effects in carrier phase double-differenced residuals, and hence improve the positioning results. Furthermore, the VLLMS filter that reduces up to about 47.4% of the multipath effects on 3D positioning performs better than the LMS filter that only reduces 22.0%. Both filters are suitable for real-time applications.     

Wavelet Shrinkage: High frequency multipath reduction from GPS relative positioning

The wavelet transform is used to reduce the high frequency multipath of pseudorange and carrier phase GPS double differences (DDs). This transform decomposes the DD signal, thus separating the high frequencies due to multipath effects. After the decomposition, the wavelet shrinkage is performed by thresholding to eliminate the high frequency component. Then the signal can be reconstructed without the high frequency component. We show how to choose the best threshold. Although the high frequency multipath is not the main multipath error component, its correction provides improvements of about 30% in pseudorange average residuals and 24% in carrier phases. The results also show that the ambiguity solutions become more reliable after correcting the high frequency multipath.     

Estimation and exclusion of multipath range error for robust positioning

In integrated systems for accurate positioning, which consist of GNSS, INS, and other sensors, the GNSS positioning accuracy has a decisive influence on the performance of the entire system and thus is very important. However, GNSS usually exhibits poor positioning results in urban canyon environments due to pseudorange measurement errors caused by multipath creation, which leads to performance degradation of the entire positioning system. For this reason, in order to maintain the accuracy of an integrated positioning system, it is necessary to determine when the GNSS positioning is accurate and which satellites can have their pseudorange measured accurately without multipath errors. Thus, the objective of our work is to detect the multipath errors in the satellite signals and exclude these signals to improve the positioning accuracy of GNSS, especially in an urban canyon environment. One of the previous technologies for tackling this problem is RAIM, which checks the residual of the least square and identifies the suspicious satellites. However, it presumes a Gaussian measurement error that is more common in an open-sky environment than in the urban canyon environment. On the other hand, our proposed method can estimate the size of the pseudorange error directly from the information of altitude positioning error, which is available with an altitude map. This method can estimate even the size of non-Gaussian error due to multipath in the urban canyon environment. Then, the estimated pseudorange error is utilized to weight satellite signals and improve the positioning accuracy. The proposed method was tested with a low-cost GNSS receiver mounted on a test vehicle in a test drive in Nagoya, Japan, which is a typical urban canyon environment. The experimental result shows that the estimated pseudorange error is accurate enough to exclude erroneous satellites and improve the GNSS positioning accuracy.     

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,…     

Characterization of the effects of high multipath phase rates in GPS

GPS multipath has been studied since the early 1970s. Prior to the investigation described in this paper, however, the effects due to the relative Doppler shift between the direct and multipath signal components have received scant attention. The single previous study that did address the issue indicated coherent receivers had significant performance advantages over noncoherent receivers. Specifically, it was stated that under the condition of fast-fading multipath, noncoherent receivers would yield a bias error, whereas coherent receivers would not. After reviewing the background theory, this paper describes a revised model of the phenomenon and shows the results of hardware simulations which validate the existence of the bias in both receiver types and offer support for the new model. A case study of a specific commercial receiver is presented. Electronic Publication     

一种GPS多路径反射信号的雪深反演

针对传统雪深测量缺乏必要时空敏感性的不足,该文在分析GPS信号多路径反射模型的基础上,利用GPS信噪比观测数据,通过分离提取多路径反射分量研究其时频特性,探讨GPS多路径信号与雪深及其变化关系并进行反演建模。依据菲涅尔反射区理论,确定了反射区域范围,进一步探讨卫星、波段选择及初始反射高度确定等。对比实验研究表明,反演结果与实测值吻合较好,相关系数为0.93,均方根误差为8.6cm;信噪比多路径反射分量的频率能有效跟踪积雪深度的变化。     

A combined algorithm of improving INS error modeling and sensor measurements for accurate INS/GPS navigation

Although the integrated system of a differential global positioning system (DGPS) and an inertial navigation system (INS) had been widely used in many geodetic navigation applications, it has sometimes a major limitation. This limitation is associated with the frequent occurrence of DGPS outages caused by GPS signal blockages in certain situations (urban areas, high trees, tunnels, etc.). In the standard mechanization of INS/DGPS navigation, the DGPS is used for positioning while the INS is used for attitude determination. In case of GPS signal blockages, positioning is provided using the INS instead of the GPS until satellite signals are obtained again with sufficient accuracy. Since the INS has a very short-time accuracy, the accuracy of the provided INS navigation parameters during these periods decreases with time. However, the obtained accuracy in these cases is totally dependent on the INS error model and on the quality of the INS sensor data. Therefore, enhanced navigation parameters could be obtained during DGPS outages if better inertial error models are implemented and better quality inertial measurements are used. In this paper, it will be shown that better INS error models are obtained using autoregressive processes for modeling inertial sensor errors instead of Gauss–Markov processes that are implemented in most of the current inertial systems and, on the other hand, that the quality of inertial data is improved using wavelet multi-resolution techniques. The above two methods are discussed and then a combined algorithm of both techniques is applied. The performance of each method as well as of the combined algorithm is analyzed using land-vehicle INS/DGPS data with induced DGPS outage periods. In addition to the considerable navigation accuracy improvement obtained from each single method, the results showed that the combined algorithm is better than both methods by more than 30%.