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.     

低成本μ-blox单频多系统GNSS接收机的定位性能分析

随着大众市场对高精度定位需求增加,基于低成本小型化设备的全球卫星导航系统(GNSS)高精度定位成为研究热点之一. 本文以低成本多系统GNSS接收机μ-blox M8P型号为例,分析其观测数据质量,研究其伪距单点定位和单频载波相对定位的定位性能和特点,为低成本GNSS接收机高精度定位应用提供参考. 实验结果表明,与测量型接收机相比,μ-blox输出GNSS观测值的载噪比略小,伪距和载波相位的测量噪声较大. 静态模式下,μ-blox的单频载波相对定位(基线长度约为430 m)可以提供厘米级的定位精度;城市环境动态模式下,其单频载波相对定位可提供亚米级至米级的定位精度. 信号受限环境下,GPS／GLONASS双系统能够提供更稳定的定位结果.      

面向北斗单历元分米级定位的ARAIM保护水平计算方法CSCD

精密定位的质量控制和完好性评估是实时全球卫星导航系统(GNSS)导航应用不可或缺的环节,尤其是在GNSS易受损害的城市峡谷等场景下,这种需求更加迫切.广域精密单点定位(PPP)瞬时分米级定位,利用GNSS三频信号形成的两个宽巷观测值可以实现单点单历元分米级定位.然而,在城市复杂环境中,反射信号、严重多路径以及其他信号干扰对定位造成的影响无法准确评估与识别,限制了PPP瞬时分米级单点定位的应用.完好性概念中的高级接收机自主完好性监测(ARAIM)可以计算用户定位误差最小置信区间的上限保护水平(PL)以评估定位有效性,可经过一定改进用于PPP瞬时定位的质量控制.针对当前ARAIM中计算PL的误差模型难以适应高精度定位需求的问题,提出了一种改进的ARAIM PL算法,称其为BARAIM(Back Advanced Receiver Autonomous Integrity Monitoring).使用PPP三频组合观测值残差对ARAIM权与误差模型进行修正以计算PL.基于不同复杂程度的环境下采集的车载数据对算法进行了验证,对PL的改进情况以及导航的可用性提升情况进行评估.结果表明:在不同环境下,基于改进的B-ARAIM算法得到的PL,相比传统方法得到的PL更符合城市定位的需要,将PL降低了30%~70%.此方法有助于将ARAIM算法应用在高精度GNSS定位领域.     

RETRACTED ARTICLE: Likelihood-based GNSS positioning using LOS/NLOS predictions from 3D mapping and pseudoranges

The accuracy of conventional global navigation satellite systems (GNSS) positioning in dense urban areas is severely degraded due to blockage and reflection of the signals by the surrounding buildings. By using 3D mapping of the buildings to aid GNSS positioning, the accuracy can be substantially improved. However, positioning performance must be balanced against computational load. Here, a likelihood-based 3D-mapping-aided (3DMA) GNSS ranging algorithm is demonstrated that enables signals predicted to be non-line-of-sight (NLOS) to contribute to the position solution without explicitly computing the additional path delay due to NLOS reception, which is computationally expensive. Likelihoods for an array of candidate positions are computed based on the difference between the measured and predicted pseudoranges. However, a skewed distribution is assumed for those signals predicted to be NLOS on the basis that the ensuing ranging errors are always positive. An overall position solution is then extracted from the likelihood surface. GNSS measurement data have been collected at several locations in both traditional and modern dense urban environments. Horizontal root-mean-square single-epoch position accuracies of 4.7, 5.6 and 6.5 m are obtained using, respectively, a Leica Viva geodetic receiver, a u-blox EVK M8T consumer-grade receiver and a Nexus 9 tablet incorporating a smartphone GNSS antenna and a GNSS chipset that outputs pseudoranges. The corresponding accuracies using single-epoch conventional GNSS positioning are 20.5, 23.0 and 28.4 m, about a factor of four larger. The 3DMA GNSS algorithms have also been implemented in real time on a Raspberry Pi 3 at a 1-Hz update rate.

     

基于小波分析提取单频GNSS伪距多路径误差及其对定位的影响

伪距多路径误差是影响GNSS导航定位精度的主要误差源之一。多路径误差与接收机周围环境有关,在实际应用中难以建立有效的多路径误差模型进行改正。对于多频GNSS接收机可以通过多频观测值组合估计伪距多路径,但该方法不适用于价格低廉的单频接收机,而导航中使用的大多数为单频接收机。因此,开展单频GNSS伪距多路径误差提取研究具有重要的工程应用价值。本文基于小波分析对单频GNSS接收机伪距多路径误差估计开展研究,首先验证了小波分析用于单频GNSS伪距多路径误差估计的可行性;其次,研究了采用不同的小波基和分解层次对多路径误差估计的影响;最后,研究了改正多路径误差对GNSS定位的影响。实验结果表明不同的小波基和分解层次对多路径误差提取效果没有明显的差别,但小波分解层次较低时定位误差分布相对更加集中,同时,经过多路径误差改正后在NEU3个方向RMS平均改善率达到20.4%、25.1%、16.4%。     

一种低成本GPS/INS紧耦合组合导航系统

描述了一种低成本的GPS/INS组合导航系统,经过理论推导得到了系统具体的实现方法,并通过市场上大量使用的低成本GPS模块和MEMS陀螺和加速度计实现了该系统。实际路测数据结果显示,该系统基本达到了理论预期。     

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.     

GPS／GLONASS／BDS多模融合伪距单点定位模型精度分析

GNSS伪距单点定位速度快且不存在整周模糊度问题,其原理简单易于编程实现,所以在进行GNSS数据处理时,经常用到该方法。本文以GPS、GLONASS、BDS多模融合为例,简单介绍多模融合存在的坐标统一、时间基准统一问题,再详细介绍多模融合伪距单点定位原理以及解算模型,基于Visual Studio2010平台,编写GPS、GLONASS、BDS多模融合的伪距单点定位及单点测速程序。结合相关算例,对该程序多系统伪距单点定位的精度以及单点测速精度进行分析。      

面向城市复杂环境的3种多频多系统GNSS单点高精度定位方法及性能分析

城市智能交通、自动驾驶等对高精度动态定位的需求为分米级甚至厘米级,但在城市复杂环境下信号遮挡、衰减和多径频繁发生,GNSS定位的可用性和精度严重降低。本文充分利用现有可用的多频多系统GNSS(GPS/BDS/Galileo/QZSS)数据,采用最新提出的单历元PPP宽巷模糊度固定方法(PPP-WAR),并与传统PPP方法和广域伪距增强精密定位方法进行对比试验,分析了这3种单点高精度定位方法在大都市高楼密布道路、小城镇狭窄道路和工业区开阔道路3种不同信号遮挡条件下的车载动态定位性能。结果表明,目前城市环境中的三频数据完整性高达94%以上,可满足基于多频GNSS单历元定位的需求。粗差阈值设定为3 m时,单历元PPP-WAR解在小城镇狭窄道路的水平定位误差RMS为0.41 m,达到了分米级定位精度,比广域伪距增强精密定位解和传统PPP解分别提高了53.9%和21.2%;3种方法在大都市高楼密布环境下的定位可用性均高于70%,在另外两种城市环境下的定位可用性均高于90%。粗差阈值0.5 m时,单历元PPP-WAR方法和传统PPP方法在小城镇狭窄道路环境中可用性依然可达~70%。单历元PPP-WAR方法受城市环境中4种典型地物(地下通道、高架桥、行道树和高楼)的影响最小。总之,在干扰因素多的城市复杂环境中单历元PPP-WAR方法更具优势,在干扰因素少的城市开阔环境中传统PPP方法更优。     

载波/多普勒平滑伪距在Android手机中的定位实现

针对Android手机GNSS伪距定位精度较低的问题,利用手机端观测信息,通过载波相位/多普勒平滑伪距改善手机端伪距观测值的质量,从而达到提高定位精度的效果。首先给出了Android手机GNSS原始观测量的获取方法,然后推导了载波相位平滑伪距和多普勒平滑伪距算法模型,并设计合理有效的试验对算法的精度进行评定。试验结果表明：在手机端静态定位中载波相位和多普勒平滑算法均可提高原始伪距的定位精度,且多普勒平滑算法表现更优;在手机端动态定位中多普勒平滑算法可获得比原始伪距更优的定位精度,但是载波相位平滑算法较原始伪距更差;由于硬件的制约手机端周跳和信号失锁严重,占比超过50%,载波相位在手机端的可用性较低;多普勒平滑算法的最优平滑时间常数小于等于10 s,具有实时动态定位的巨大潜力。     

城市场景智能手机GNSS/MEMS融合车载高精度定位

智能手机凭借其普遍性、便携性和低成本等优势,已成为大众用户导航与位置服务的主流终端载体,其多频多系统GNSS（global navigation satellite system）观测值的开放进一步激发了手机高精度定位的研究。然而,受限于消费级GNSS器件性能,手机卫星观测值呈现出信号衰减严重、伪距噪声大、粗差周跳多等问题;并且受城市复杂环境影响,手机GNSS定位的连续性、可靠性也难以保证。提出一种城市场景手机GNSS/ MEMS（micro-electro mechanical system）融合的车载高精度定位方案。首先,构建了速度约束的GNSS差分定位模型;然后,通过手机内置MEMS与车辆运动约束,在挑战环境下进行GNSS/MEMS融合精密定位。实验结果表明,在开阔和树荫场景下,速度约束方法可达到分米至米级定位精度,相比于常规方法分别提升了35.2%和78.9%;在高架场景下,GNSS/MEMS融合定位的精度和连续性均提升显著;在隧道场景下,MEMS推算位置累积误差约为2.5%。实验结果初步表明,手机GNSS具备开阔环境下的车道级定位能力,手机GNSS/MEMS融合可提升城市复杂环境下车载定位的精度和连续可用性。     

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.     

A closed-loop EKF and multi-failure diagnosis approach for cooperative GNSS positioning

Current cooperative positioning with global navigation satellite system (GNSS) for connected vehicle application mainly uses pseudorange measurements. However, the positioning accuracy offered cannot meet the requirements for lane-level positioning, collision avoidance and future automatic driving, which needs real-time positioning accuracy of better than 0.5 m. Furthermore, there is an apparent lack of research into the integrity issue for these new applications under emerging driverless vehicle applications. In order to overcome those problems, a new extended Kalman filter (EKF) and a multi-failure diagnosis algorithm are developed to process both GNSS pseudorange and carrier phase measurements. We first introduce a new closed-loop EKF with partial ambiguity resolution as feedback to address the low accuracy issue. Then a multi-failure diagnosis algorithm is proposed to improve integrity and reliability. The core of this new algorithm includes using Carrier phase-based Receiver Autonomous Integrity Monitoring method for failure detection, and the double extended w test detectors to identify failure. A cooperative positioning experiment was carried out to validate the proposed method. The results show that the proposed closed-loop EKF can provide highly accurate positioning, and the multi-failure diagnosis method is effective in detecting and identifying failures for both code and carrier phase measurements.     

高遮挡环境下卫星数不足四颗的GPS定位研究

讨论了GPS接收机观测卫星数不足4颗条件下的GPS导航定位问题，提出拟合外推接收机钟差，联合大地高，地图匹配的方法，推导了相应的数学模型，并编程实现其算法，对实际车载动态GPS数据进行解算。解算结果表明：利用上述方法可以解决观测卫星数不足4颗条件下的GPS导航定位问题。     

多GNSS融合伪距单点定位算法及其程序实现

随着GNSS技术的发展,目前具备独立服务能力的系统包括GPS、GLONASS和BDS。针对多GNSS融合导航定位的成为近几年研究的热点这一现象,本文对基于Visual Studio 2010 C++平台编写多GNSS融合伪距单点定位程序中出现的关键点做了详细叙述,详述了多GNSS伪距单点定位模型以及部分测量误差的改正,通过实例计算验证了多系统单点定位可以改善卫星结构,提高系统在复杂环境下测量时的稳定性,从而验证了程序的正确性与可行性。     

BDS/GPS网络差分定位试验分析

针对在传统网络差分定位中,单GPS系统在观测条件不好情况下会出现可用卫星数量偏少甚至不够、观测值存在粗差而影响定位等问题,该文提出BDS/GPS双系统组合网络伪距差分定位的数学模型,并加入基于最小二乘残差法探测粗差观测数据的质量控制算法。基于省CORS网实时BDS/GPS双系统数据,以国产的手持机终端作为流动端,利用BDS/GPS伪距差分平台进行了车载动态试验,根据试验对比和分析,动态定位平面精度优于1m,在加入质量控制算法模式下,定位精度和可靠性都有一定提高。     

Simultaneous estimation of GLONASS pseudorange inter-frequency biases in precise point positioning using undifferenced and uncombined observations

GLONASS precise point positioning (PPP) performance is affected by the inter-frequency biases (IFBs) due to the application of frequency division multiple access technique. In this contribution, the impact of GLONASS pseudorange IFBs on convergence performance and positioning accuracy of GLONASS-only and GPS + GLONASS PPP based on undifferenced and uncombined observation models is investigated. Through a re-parameterization process, the following four pseudorange IFB handling schemes were proposed: neglecting IFBs, modeling IFBs as a linear or quadratic polynomial function of frequency number, and estimating IFBs for each GLONASS satellite. One week of GNSS observation data from 132 International GNSS Service stations was selected to investigate the contribution of simultaneous estimation of GLONASS pseudorange IFBs on GLONASS-only and combined GPS + GLONASS PPP in both static and kinematic modes. The results show that considering IFBs can speed up the convergence of PPP using GLONASS observations by more than 20%. Apart from GLONASS-only kinematic PPP, the positioning accuracy of GLONASS-only and GPS + GLONASS PPP is comparable among the four schemes. Overall, the scheme of estimating IFBs for each GLONASS satellite outperforms the other schemes in both convergence time reduction and positioning accuracy improvement, which indicates that the GLONASS IFBs may not strictly obey a linear or quadratic function relationship with the frequency number.     

手机GNSS数据质量提取的变分模态分解法

观测噪声提取是数据质量分析与随机模型构建的基础。当前手机GNSS观测噪声提取主要采用三阶差分法与历元间差分法,这些方法的提取结果都会受到卫星相关性和历元间相关性的影响。本文提出结合变分模态分解(variational mode decomposition,VMD)提取手机观测噪声的方法。模拟分解试验表明:VMD能够较好地对混合信号进行分解。提取小米8手机GNSS观测噪声并进行分析,结果表明:GPS、BDS和Galileo 3系统伪距观测噪声计算结果一致,GLONASS系统伪距噪声大约是其他系统的两倍,四系统的载波观测噪声相当,手机GNSS观测噪声与Android系统版本无关。相比于高度角随机模型,载噪比随机模型更适用于手机GNSS定位。利用数据质量提取结果拟合载噪比随机模型,并进行定位试验。定位结果表明:相对于高度角随机模型,采用载噪比随机模型后手机伪距单点定位效果能提升25%以上。手机PPP平面定位结果能收敛至0.6 m以内,高程定位精度收敛至1.2 m以内。     

卫星信号发射时刻的无偏恢复

卫星信号发射时刻在导航定位中是一个重要的参数,但是在城市峡谷等弱信号条件下,接收机可能完成不了所有卫星信号发射时刻的组装。在伪距定位中卫星信号发射时刻的组装和粗时段导航中卫星信号发射时刻的恢复(有偏)技术基础上,提出一种无偏的卫星信号发射时刻恢复方法,前提是卫星至少能完成一颗星的伪距测量,并且具有150km误差范围内的先验位置和辅助星历。利用BDS B1和GPS L1中频数据在软件接收机平台进行了BDS,GPS信号发射时刻无偏恢复验证实验证明了方法的有效性。     

谷歌Nexus 9智能终端原始GNSS观测值的质量分析

从信噪比、伪距残差、相位残差等方面对开阔环境下的静态谷歌Nexus 9智能平板终端的原始全球导航卫星系统（Global Navigation Satellite System,GNSS）观测数据质量进行了分析评估,结果表明,Nexus 9平板的全球定位系统（Global Positioning System,GPS）、GLONASS观测值的信噪比比测量型接收机低10 dBHz左右;伪距精度分别为5.43 m、11.39 m,相位精度分别为4.44 mm、4.99 mm;相对于高度角来说,信噪比与伪距残差的相关性更强,更能反映观测数据的质量。在此基础上给出了信噪比定权的随机模型,并进行了开阔环境下的伪距单点定位测试。实验结果表明,基于信噪比定权的单点定位平面精度为2.74 m,高程精度为4.56m,比高度角定权精度提高了约26%。