基于高度角的多路径误差改正方法

多路径效应是影响卫星定位的主要误差源之一,是GNSS领域研究的热点和难点问题。本文针对现有多路径误差改正方法存在通用性弱、计算结果受噪声影响大等不足,本文提出了基于卫星高度角的多路径误差改正方法,并通过实验验证了该方法对改正静态多路径误差具有可行性。结果表明,通过应用该模型,四系统组合伪距单点定位精度提升幅度可达15%左右,相较于基于周跳探测的双频伪距载波组合提取多路径误差的方法,基于高度角的方法运算简便,抗干扰能力更好。     

GPS变形监测中多路径效应的削弱方法研究

主要从GPS的基本观测方程出发,通过数学分析的方法,在GPS观测值之间建立数学模型,进一步分别推导了伪距观测值和相位观测值中多路径效应的影响。此外,主要研究了利用相位平滑伪距削弱伪距多路径误差的方法和利用小波分析的方法对GPS多路径值序列进行分解和重构,提取出高精度的多路径误差,并通过实验数据分析了几种方法中的多路径效应影响。     

变形监测中GPS多路径效应的削弱方法研究

本文主要从GPS的基本观测方程出发,通过数学分析的方法,在GPS观测值之间建立数学模型,进一步推导了伪距观测值和相位观测值中多路径效应的影响.此外,主要研究了利用相位平滑伪距削弱伪距多路径误差的方法,以及利用小波分析的方法对GPS多路径值序列进行分解和重构,提取出高精度的多路径误差,并通过实验数据分析了几种方法中的多路径效应.     

单频到五频多系统GNSS精密单点定位参数估计与应用

全球导航卫星系统(GNSS)已发展至多频多系统时代,特别以我国北斗卫星导航系统(BDS)为代表的四大全球导航卫星系统可全天时、全天候播发十几个频率的伪距、相位和多普勒等观测信息。多频多系统GNSS为用户提供更多的观测数据和组合选择,为精密定位、导航和授时(PNT)应用带来了新的机遇,如高精度位置服务、大地测量、空间天气和灾害监测等。但多频多系统GNSS观测为精密单点定位(PPP)组合模型和系统偏差及大气延迟估计等带来诸多问题和挑战。本文给出了单频到五频多系统GNSS精密单点定位(PPP)模型,估计和评估了单频到五频多系统GNSS PPP定位精度、接收机钟差、对流层延迟、卫星和接收机硬件延迟,以及频间偏差。给出了GNSS PPP最新应用进展,包括GNSS气象学、电离层模拟、时间频率传递、建筑物安全和地震监测及其应用。结果表明,多频多系统极大地提高了GNSS PPP参数估计的精度和可靠性,具有重要的应用价值。最后给出了多频多系统GNSS PPP应用前景与展望。     

城市典型环境下单频导航型GNSS接收机多路径误差特性分析

在高大建筑物、树木遮挡等城市复杂环境中,多路径误差和纯反射(NLOS)信号误差难以准确建模,严重影响行人GNSS导航定位的精度和可用性。本文首先对比分析了多路径延迟和纯反射信号延迟的误差特性,然后利用双差观测方程提取多路径和NLOS延迟误差,分析了两种延迟误差对伪距、载波相位和多普勒观测值的影响。通过UBLOX-NEO-M8T单频导航型接收机在建筑物附近和树木遮挡两种观测环境下的实测数据处理与分析,结果表明:载噪比(C/N0)较小时多普勒噪声明显变大。对于M8T导航型接收机,多路径影响严重的环境下C/N0低于30 d BHz,多普勒噪声变大。而NLOS影响严重的环境下多普勒噪声与C/N0之间关系不明显,在较大的C/N0,多普勒噪声仍然很大;在树木遮挡时,主要受多路径效应的影响,引起伪距的误差量级在10~150 m之间,对相位和多普勒的影响不明显;在高楼遮挡时,会出现NLOS信号干扰,对伪距和载波相位观测值的影响相同,延迟量大小与反射点的距离有关,可达到几百米,对多普勒观测值也有明显影响。     

GPS伪距改正及精密动态单点定位精度分析

给出了GPS伪距定位在动态模式下的改正模型：对流层折射延迟、电离层延迟改正、地球自转改正、相对论效应改正、卫星天线和接收机天线改正、固体潮改正。并针对单频GPS接收机进行动态伪距定位的试验，分析了各项改正对GPS伪距定位的精度影响及综合改正后的精度分析。     

改进的GPS/BDS的RTK定位性能分析

针对多路径误差作为短基线GNSS定位的主要误差来源,不能在传统双差模型中有效消除的问题,该文基于小波分解和重构,提出了一种对伪距和载波相位观测值中多路径误差有效提取和剔除的算法,探讨剔除后GPS/BDS双系统的RTK定位精度和可靠性。结果表明,伪距多路径误差和载波相位多路径误差量级分别为米级和厘米级,主要集中在低频滤波中,且提取后的残余随机噪声趋于稳定。此算法能较好地剔除和提取多路径误差,提高整周模糊度解算速度,达到理想的滤波效果,且通过迭代扩展的卡尔曼滤波处理后,坐标离散更小,X、Y、Z外符合精度均达到厘米级。     

三频电离层延迟改正中多路径误差和观测噪声的削弱算法

多频测距系统可以借助多频观测数据削弱电离层延迟的影响,但多频改正算法在改正电离层延迟项的同时会不同程度地放大多路径误差、观测噪声等伪距误差的影响。其中利用三频数据可以将电离层延迟改正至二阶项,也可以只改正至一阶项,分别称为三频二阶改正和三频一阶改正。首次推导了利用三频观测数据削弱伪距中多路径效应和观测噪声等误差的算法,使三频电离层延迟改正中伪距误差的影响大大减小。通过对三频实测数据的处理和分析验证了算法的有效性并给出了一些有益的结论和建议:在利用三频观测数据进行电离层改正时,首先改正伪距中的多路径误差和观测噪声,然后采用三频二阶改正算法将电离层延迟改正至二阶项,将有效提高伪距改正精度。如果不能有效削弱这些误差的影响,宜采用三频一阶改正或双频改正。     

GNSS接收机伪距偏差确定方法及其对定位的影响

全球导航卫星系统（global navigation satellite system,GNSS）接收机伪距偏差是指卫星导航信号非理想特征导致的不同接收机的伪距测量常数偏差。研究表明,接收机伪距偏差无法被钟差参数吸收,将影响GNSS精密应用。选取了多GNSS实验全球跟踪网的9条零/短基线,将基线按照接收机类型分为3组,即相同厂商相同型号、不同厂商以及相同厂商不同型号,通过双差法确定了每组基线GPS/北斗卫星导航系统(BeiDou satellite navigation system,BDS)/伽利略卫星导航系统（Galileo satellite navigation system,Galileo）的接收机伪距偏差,并分析了接收机伪距偏差的稳定性及其对整周模糊度解算和伪距相对定位的影响。结果表明,不同厂商接收机构成的基线,伪距偏差可达160 cm,即使同一厂商不同型号的接收机间也存在不可忽略的伪距偏差;对于GPS、BDS和Galileo,Galileo伪距偏差最小,BDS伪距偏差最大。此外,接收机伪距偏差具有良好的稳定性,60 d标准差不超过12 cm。接收机伪距偏差改正后,GPS、...     

北斗三号卫星导航信号接收机端伪距偏差建模与验证

接收机端伪距偏差是指非理想的卫星导航信号在接收机前端带宽和相关器间隔不同时产生的伪距测量系统性偏差。研究表明,北斗二号、GPS和Galileo系统均存在与接收机类型相关的伪距偏差,影响基于混合类型接收机站网的精密数据处理。本文基于iGMAS网和MGEX网观测数据,采用MW组合、伪距残差和伪距无几何距离无电离层组合3种方法分析北斗三号接收机端伪距偏差特性。试验结果表明,北斗三号同样存在与接收机类型相关的伪距偏差,且无电离层组合的伪距偏差可以达到6 ns。根据偏差特性,按接收机类型建立了8类伪距偏差改正模型。将上述模型应用于卫星差分码偏差(DCB)估计与单频伪距单点定位,结果表明,模型改正后可以显著提升不同接收机类型估计的卫星DCB一致性,其中基于iGMAS网和MGEX网两个不同接收机站网估计得到的北斗三号C2I-C6I、C1P-C5P和C2I-C7D DCB差值分别平均降低了91.6%、64.7%和71.9%;模型改正后单频伪距单点定位水平方向和高程方向精度分别提升了13.9%和11.0%。     

GNSS接收机观测数据多径效应分析方法研究

多径效应是影响GNSS接收机观测数据质量的主要误差因素之一。首先,介绍了多径效应及其信号特性,分析了多径效应对GNSS接收机伪距测量和载波相位测量的影响,阐述了三种GNSS接收机观测数据多径效应分析方法,并结合实际观测数据给出了多径效应分析结果,最后介绍了几种常用的多径效应抑制方法。     

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.     

A study on the dependency of GNSS pseudorange biases on correlator spacing

We provide a comprehensive overview of pseudorange biases and their dependency on receiver front-end bandwidth and correlator design. Differences in the chip shape distortions among GNSS satellites are the cause of individual pseudorange biases. The different biases must be corrected for in a number of applications, such as positioning with mixed signals or PPP with ambiguity resolution. Current state-of-the-art is to split the pseudorange bias into a receiver- and a satellite-dependent part. As soon as different receivers with different front-end bandwidths or correlator designs are involved, the satellite biases differ between the receivers and this separation is no longer practicable. A test with a special receiver firmware, which allows tracking a satellite with a range of different correlator spacings, has been conducted with live signals as well as a signal simulator. In addition, the variability of satellite biases is assessed through zero-baseline tests with different GNSS receivers using live satellite signals. The receivers are operated with different settings for multipath mitigation, and the changes in the satellite-dependent biases depending on the receivers’ configuration are observed.     

基于北斗GEO的电离层延迟修正方法比较与分析

电离层延迟是影响导航定位精度的最主要因素。北斗卫星导航系统采用Klobuchar模型修正单频接收机用户的电离层延迟误差,对于双频接收机,可以利用不同频率信号的伪距观测数据解算得到电离层延迟值。为比较两种方法在天津地区的电离层延迟修正效果,利用NovAtel GPStation6接收机(GNSS电离层闪烁和TEC监测接收机)采集到的卫星实测数据进行计算。以国际全球导航卫星系统服务组织(IGS)发布的全球电离层格网数据为参考,对两种方法的修正效果进行比较分析。结果表明,在天津地区,利用双频观测值解算电离层延迟比Klobuchar模型计算结果更加精确,且平均每天的修正值达到IGS发布数据的82.11％,比Klobuchar模型计算值高948％      

Comparison of 4D tomographic mapping versus thin-shell approximation for ionospheric delay corrections for single-frequency GPS receivers over North America

The majority of navigation satellite receivers operate on a single frequency. They compensate for the ionospheric delay using either an ionospheric model which typically only corrects for 50% of the delay or a thin-shell map of the ionosphere. A 4D tomographic imaging technique is used to map the free electron density over the full-height of the ionosphere above North America during autumn 2003. The navigation solutions computed using correction based upon the thin-shell and the full-height maps are compared in this paper. The maps are used to calculate the excess propagation delay on the L1 frequency experienced by GPS receivers at selected locations across North America. The excess delay is applied to correct the single-frequency pseudorange observations at each location, and the improvements to the resulting positioning are calculated. It is shown that the thin-shell and full-height maps perform almost as well as a dual-frequency carrier-smoothed benchmark and for most receivers better than the unfiltered dual-frequency benchmark. The full-height corrections perform well and are considerably better than thin-shell corrections under extreme storm conditions.     

A new multipath mitigation method based on adaptive thresholding wavelet denoising and double reference shift strategy

Multipath disturbance is one of the major error sources in high-accuracy positioning for global navigation satellite system (GNSS). Although various methods based on software and hardware strategies have been developed to mitigate this error, they are still limited by different kinds of factors and the effect is not ideal. After analyzing the existing methods, a new single-difference sidereal filtering method, based on adaptive thresholding wavelet denoising and double reference shift strategy (ATDR), is proposed to mitigate multipath effects for static short-baseline GNSS applications. The key idea of the proposed method is the use of both the adaptive thresholding wavelet denoising to extract an accurate multipath correction model from the reference Day and the double reference shift strategy to mitigate multipath for subsequent Day 2 more accurately and efficiently. By applying the introduced adaptive thresholding method, the average improvement rate of the RMS values of the single-difference residuals can reach about 15.82% compared with the constant thresholding method. Moreover, after applying the proposed ATDR method, the 3D positioning precision is improved by about 37.73% for the single epoch mode with 30 s data sampling rate and about 31.22% for the continuous mode with 1 s high sampling rate compared with the original results. Even compared with the constant thresholding single orbital reference (CTSR) method, the improvement percentage is about 33.94% in single epoch mode and about 25.40% in continuous mode for 3D positioning precision, respectively. In conclusion, the results of the two experiments indicate that the proposed ATDR method performs much better than the CTSR method in mitigating multipath for different sampling rates and different processing modes in the measurement domain for GNSS static short-baseline postprocessing applications.     

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.     

Evaluation of three ionospheric delay computation methods for ground-based GNSS receivers

GNSS observables for ionospheric estimation are commonly based on carrier-to-code leveling (CCL) and precise point positioning (PPP) methods. The CCL method is a geometry-free method which uses carrier phase to level pseudorange observation for decreasing multipath error and observation noise. However, the ionospheric observable based on the CCL has been proven to be affected by leveling errors. The leveling errors are caused by pseudorange multipath and intraday variation of receiver DCB. To obtain more accurate ionospheric observable, the PPP method takes advantage of precise satellite-to-ground range for retrieving slant total electron content and is less affected by the leveling errors. Previous studies have only proven that the ionospheric observables extracted by the two methods are affected by the leveling errors. The influence on ionospheric observable by the pseudorange inter-receiver satellite bias (IRSB) of the receiver has not been taken into consideration. Also, the magnitude of the differences between the ionospheric observables extracted by the two methods has also not been given. In this work, three methods, namely, the CCL, the conventional ionospheric-free PPP method which uses the ionospheric-free Hatch–Melbourne–Wubbena (HMW) function, and the University of Calgary (UOFC) PPP method, are selected to analyze and compare the differences of ionospheric observables and the global ionospheric maps, using a large number of measured data from international GNSS service global stations. Experimental results show that the accuracy of ionospheric observables obtained by the three methods is not only related to the leveling error, but also pseudorange IRSB. The IRSB of the receiver exerts a major effect on the ionospheric observables obtained by the CCL method and a minor effect on the ionospheric observables obtained by the HMW and UOFC methods. The accuracies in the latter case are similar and superior to those obtained by the CCL. The differences of the ionospheric observables obtained by the CCL and UOFC methods, or the CCL and HMW methods, are at decimeter level, whereas the difference of the ionospheric observables obtained by the UOFC and HMW methods is at centimeter level. The UOFC method presented the highest single-frequency pseudorange positioning accuracy using estimated global ionospheric products, followed by the HMW and the CCL methods which presented the lowest positioning accuracy.     

Ionospheric error contribution to GNSS single-frequency navigation at the 2014 solar maximum

For single-frequency users of the global satellite navigation system (GNSS), one of the main error contributors is the ionospheric delay, which impacts the received signals. As is well-known, GPS and Galileo transmit global models to correct the ionospheric delay, while the international GNSS service (IGS) computes precise post-process global ionospheric maps (GIM) that are considered reference ionospheres. Moreover, accurate ionospheric maps have been recently introduced, which allow for the fast convergence of the real-time precise point position (PPP) globally. Therefore, testing of the ionospheric models is a key issue for code-based single-frequency users, which constitute the main user segment. Therefore, the testing proposed in this paper is straightforward and uses the PPP modeling applied to single- and dual-frequency code observations worldwide for 2014. The usage of PPP modeling allows us to quantify—for dual-frequency users—the degradation of the navigation solutions caused by noise and multipath with respect to the different ionospheric modeling solutions, and allows us, in turn, to obtain an independent assessment of the ionospheric models. Compared to the dual-frequency solutions, the GPS and Galileo ionospheric models present worse global performance, with horizontal root mean square (RMS) differences of 1.04 and 0.49 m and vertical RMS differences of 0.83 and 0.40 m, respectively. While very precise global ionospheric models can improve the dual-frequency solution globally, resulting in a horizontal RMS difference of 0.60 m and a vertical RMS difference of 0.74 m, they exhibit a strong dependence on the geographical location and ionospheric activity.