扩展卡尔曼滤波的虚拟格网伪距差分算法研究

针对传统伪距差分服务端压力大,以及在复杂环境下进行导航定位,某些历元卫星信号弱、卫星数不足、无法连续定位的问题,该文提出了基于扩展卡尔曼滤波算法的虚拟格网伪距差分方法。该方法充分利用先验信息和动力学模型,解决了复杂环境中动态定位结果不连续、定位精度低等问题。为验证算法的有效性,该文分别进行了动态、静态实验,并与最小二乘结果进行对比,实验结果表明:静态模式下,卡尔曼滤波算法比最小二乘算法的定位精度,在N、E、U方向分别提高48.3%、47.1%、52.5%;动态模式下,卡尔曼滤波算法比最小二乘算法更加稳定,更适合复杂环境定位。     

精密单点定位用户自主式完备性监测算法

精密单点定位PPP是当前GNSS高精度定位中的关键技术之一,使用的PPP采用扩展卡尔曼滤波估计,未知参数包括站点坐标,接收机钟差,对流层延迟以及虚拟未知数。在QR奇偶检校法的基础上,重点考察设计矩阵向量间的相关距离,将其作为粗差探测和识别的研究对象。通过向量相关距离时间序列,可以区分单个粗差和多个粗差的粗差集。提出精密单点定位的RAIM算法,解决了精密单点定位中的质量控制问题,使得多个粗差的识别更加清晰和快捷。     

利用接收机钟差实时滤波提高GNSS精度

建立接收机钟差的高斯马尔可夫模型,通过自相关函数估计接收机钟差的时间常数,利用Allan方差确定模型谱密度参数,将滤波后的接收机钟差返回补偿至GNSS观测方程,重新进行导航解算。实验结果表明,对接收机钟差进行滤波,可有效提高钟差估计精度,提高GNSS的精度。     

高性能原子钟钟差建模及其在精密单点定位中的应用

鉴于当前许多IGS跟踪站均配置有高性能原子钟的现状,本文首先采用修正Allan方差法分析了不同IGS跟踪站的接收机钟随机噪声的时域特性,进而评估了不同类型接收机的短期稳定度及钟差建模的可行性,然后利用IGS站配有氢原子钟的观测数据,在精密单点定位算法中,通过对钟差参数进行短时建模约束接收机钟差的随机变化,进而改进精密单点定位(PPP)的定位性能。试验结果表明钟差建模方法显著降低了高程分量参数、天顶对流层延迟参数与接收机钟差参数之间的相关性,GNSS高程分量的精度可提高50%。该方法对于提升PPP技术在地壳形变监测、低轨卫星定轨、水汽监测及预报等高精度GNSS地学领域的应用水平具有一定意义。     

卡尔曼滤波的中长基线非差RTK算法

针对实时动态定位(RTK)中作业范围受到大气延迟误差制约的现象,该文提出了一种基于卡尔曼滤波的非差观测模型RTK算法和非差改正数的计算方法。利用扩展卡尔曼滤波函数模型,将残余的相对对流层延迟、相对电离层延迟同流动站位置参数以及单差整周模糊度作为状态向量进行卡尔曼滤波估计。非差观测模型利用参考站的非差误差改正数以单颗卫星为对象进行误差改正,流动站接收数据小,算法简单。通过GNSS实测数据对该算法进行了算法验证和结果分析,实验结果表明,对于中长基线,利用非差观测模型可实现GNSS单参考站RTK定位,并获得厘米级的定位精度。     

基于噪声估计的卡尔曼滤波用于GPS卫星钟差预报研究

利用重叠哈达玛方差确定卫星钟噪声随机模型,采用顾及钟差随机噪声模型的卡尔曼滤波进行钟差预报分析,并与最小二乘预报算法相比较,得出以下结论:卡尔曼滤波进行1 d以内的短期预报时,精度达到亚纳秒级,优于最小二乘预报算法,在长期预报或拟合数据量较少时,最小二乘预报精度优于卡尔曼滤波。     

基于GNSS多径信号的反射面参数估计算法

全球卫星导航系统（GNSS）多径信号广泛存在于城市峡谷等复杂导航定位场景中. 多径信号在干扰GNSS接收机并造成系统定位精度下降的同时,也为接收机提供了周边反射面环境信息. 在码相位延迟幅度联合跟踪算法（CADLL）实现GNSS多径信号感知和特征参数提取的基础上,设计实现了基于粒子滤波的反射面参数估计算法. 该算法可以在GNSS多径环境中增强接收机的环境感知能力,相关环境信息可应用于场景感知、避障、路径规划和定位增强等领域. 静态环境下进行GNSS多径信号采集和算法测试,实验结果表明该算法能够有效估计反射面位置参数,反射面方位角均方根误差（RMSE）小于10°,反射面俯仰角RMSE小于5°,反射面距离RMSE小于10 m.      

抗差序贯最小二乘法在GNSS定位中的应用研究

提出了一种基于历史定位信息优化首次定位精度的方法。GNSS终端需要进行重新定位的情况十分常见,比如驾车至停车场,驶离时需要重新开启导航。在城区,信号环境通常较复杂,存在可见星数目少,卫星几何构型差且受多径效应影响,定位精度会出现较大误差。因此,提高首次定位精度的研究能够有效提升用户体验。实际上,在发起重定位时,接收机通常记录之前的历史定位信息,利用这些信息作为附加条件参与定位解算可以有效提升定位精度。据此,提出的序贯最小二乘法充分利用了这些历史定位信息,采用稳健估计方法,进一步增强抗差能力。实验结果表明。     

北斗/GPS实时精密卫星钟差融合解算模型及精度分析

实时GNSS精密单点定位(PPP)技术必须使用实时的高精度卫星精密轨道和钟差。本文研究了精密卫星钟差融合解算模型及策略,并利用滤波算法实现了北斗/GPS实时精密卫星钟差融合估计算法。仿真实时试验结果显示:获得的北斗/GPS实时钟差与GFZ事后多GNSS精密钟差(GBM)的标准差在0.15 ns左右;使用该钟差进行GPS动态PPP试验,收敛后水平精度优于5 cm,高程精度优于10 cm;使用仿真实时钟差进行的北斗动态PPP与使用GFZ事后多GNSS精密钟差开展的试验相比精度相当,可实现分米级定位。     

附加原子钟物理模型的PPP时间传递算法

传统精密单点定位(PPP)时间传递算法通常把接收机钟差当作相互独立的白噪声逐历元进行估计,而忽略了钟差参数历元间的相关性。针对这一问题,本文提出了一种附加原子钟物理模型的PPP时间传递算法。该算法通过利用Kalman滤波对高稳定度的原子钟钟差进行建模,拓展传统PPP时间传递模型中的接收机钟差参数,并给出了Kalman滤波过程噪声协方差和初始状态向量的确定方法。试验结果表明:该算法可以有效避免传统算法时间传递结果需要一定收敛时间的问题,使解算结果更加符合原子钟的物理特性,能够显著提高时间传递结果的精度和稳定性,可将单站时间传递精度平均提高58%,站间时间传递精度平均提高51%。     

基于GNSS精密单点定位的高精度云平台授时

采用GNSS精密单点定位(PPP)技术和时钟驯服技术,构建了基于PPP的云平台高精度授时方案,研制了搭载多系统GNSS接收机板卡、恒温晶振(OCXO)和数字信号处理器(DSP)的授时原理样机。利用协同精密定位平台分析中心(武汉)提供的5 s间隔卫星轨道和钟差产品,采用PPP技术实时解算授时终端坐标和钟差,通过驯服恒温晶振输出亚纳秒精度的1 PPS,实现了长时间高精度的授时能力。本文通过短基线比较和与UTC绝对时间基准比较,验证了精密单点授时精度(RMS)优于1 ns。     

GLONASS pseudorange inter-channel biases considerations when jointly estimating GPS and GLONASS clock offset

GLONASS clock offset estimation is affected by the inter-channel biases (ICBs) caused by frequency division multiple access technique. The effect of ICBs on joint GPS/GLONASS clock offset estimation is analyzed. An efficient approach for joint estimation of GPS/GLONASS satellite clock offset is applied to the generation of 30-s clock offset products. During the estimation, the following three ICB handling strategies were tested: calculating ICBs for each GLONASS signal channel, calculating ICBs for each GLONASS satellite and neglecting ICBs. The behavior of ICBs under different strategies was statistically stable. Subsequently, the clock offset products using different ICB strategies were evaluated. The evaluation shows that consideration of the ICB is important when estimating the clock offset. Furthermore, estimating one ICB for each GLONASS satellite is better than estimating one for each GLONASS signal channel because, with the former strategy, the clock offset products behave more smoothly and have higher accuracy compared with products from the International GNSS Service Analysis Center. In addition, precise point positioning, using clock offsets based on one ICB for each GLONASS satellite, has the highest positioning accuracy.     

Method for evaluating real-time GNSS satellite clock offset products

Real-time satellite clock offset products are frequently utilized in navigation and positioning service fields. The precision of such products is a key issue for their application. The evaluation methods existed for satellite clock offset products are mostly based on post-processed satellite clock offset solutions, which will encounter problems in real-time product evaluation, especially for real-time satellite clock offset products estimated from data with regional stations only. We propose an improved evaluation method for global navigation satellite system (GNSS) satellite clock offset products. In the proposed method, we use all-satellite reference method instead of single-satellite reference method to eliminate the timescale in satellite clock offset products. Moreover, a preprocessing step is suggested to detect gross errors and initial clock bias before evaluating the precision of the satellite clock offsets. We conduct two examples to verify our method, and the experimental results show that the proposed method is more reasonable in assessing the GNSS satellite clock offset precision, and it also provides a reliable approach to analyzing the estimated satellite clock offset in both real-time and post-processed, or globally and regionally.     

A reference station-based GNSS computing mode to support unified precise point positioning and real-time kinematic services

Currently, the GNSS computing modes are of two classes: network-based data processing and user receiver-based processing. A GNSS reference receiver station essentially contributes raw measurement data in either the RINEX file format or as real-time data streams in the RTCM format. Very little computation is carried out by the reference station. The existing network-based processing modes, regardless of whether they are executed in real-time or post-processed modes, are centralised or sequential. This paper describes a distributed GNSS computing framework that incorporates three GNSS modes: reference station-based, user receiver-based and network-based data processing. Raw data streams from each GNSS reference receiver station are processed in a distributed manner, i.e., either at the station itself or at a hosting data server/processor, to generate station-based solutions, or reference receiver-specific parameters. These may include precise receiver clock, zenith tropospheric delay, differential code biases, ambiguity parameters, ionospheric delays, as well as line-of-sight information such as azimuth and elevation angles. Covariance information for estimated parameters may also be optionally provided. In such a mode the nearby precise point positioning (PPP) or real-time kinematic (RTK) users can directly use the corrections from all or some of the stations for real-time precise positioning via a data server. At the user receiver, PPP and RTK techniques are unified under the same observation models, and the distinction is how the user receiver software deals with corrections from the reference station solutions and the ambiguity estimation in the observation equations. Numerical tests demonstrate good convergence behaviour for differential code bias and ambiguity estimates derived individually with single reference stations. With station-based solutions from three reference stations within distances of 22–103 km the user receiver positioning results, with various schemes, show an accuracy improvement of the proposed station-augmented PPP and ambiguity-fixed PPP solutions with respect to the standard float PPP solutions without station augmentation and ambiguity resolutions. Overall, the proposed reference station-based GNSS computing mode can support PPP and RTK positioning services as a simpler alternative to the existing network-based RTK or regionally augmented PPP systems.     

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。     

同时估计电离层延迟的单频精密单点定位方法

提出一种基于单频码和相位观测量的单频精密单点定位方法,将每个观测量的电离层延迟量与接收机钟差、对流层天顶延迟、接收机位置、相位模糊度一起作为未知参数。采用约化参数的平方根信息滤波与平滑算法进行参数解算。该方法适用于实时定位和事后处理,且不需要外部的电离层模型。采用全球分布的32个IGS监测站16 d实测数据进行静态解算试验,结果表明E、N、U方向的RMS分别为0.023 m、0.018 m、0.059 m;基于一组机载GPS数据进行动态解算试验,得到E、N、U方向的RMS(与载波相位动态相对定位结果比较)分别为0.168 m、0.151 m、0.172 m。     

Single epoch estimation of the Galileo integrity chain sensor station clock offsets

The Galileo integrity chain depends on a number of key factors, one of which is contamination of the signal-in-space errors with residual errors other than imperfect modelling of satellite orbits and clocks. A potential consequence of this is that the user protection limit is driven not by the errors associated with the imperfect orbit and clock modelling, but by the distortions induced by noise and bias in the integrity chain. These distortions increase the minimum bias the integrity chain can guarantee to detect, which is reflected in the user protection limit. A contributor to this distortion is the inaccuracy associated with the estimation of the offset between the Galileo sensor station (GSS) receiver clocks and the Galileo system time (GST). This offset is termed the receiver clock synchronization error (CSE). This paper describes the research carried out to determine both the CSE and its associated error using GPS data as captured with the Galileo System Test Bed Version 1 (GSTB-V1). In the study we simulate open access to a time datum using IGS data. Two methods are compared for determining CSE and the corresponding uncertainty (noise) across a global network of tracking stations. The single-epoch single-station method is an ‘averaging’ technique that uses a single epoch of data, and is carried out at individual sensor stations, without recourse to the data from other stations. The global network solution method is also single epoch based, but uses the inversion of a linearised model of the global system to solve for the CSE simultaneously at all GSS along with a number of other parameters that would otherwise be absorbed into the CSE estimate in the averaging technique. To test the effectiveness of various configurations in the two methods the estimated synchronisation errors across the GSS network (comprising 25 stations) are compared to the same values as estimated by the International GPS Service (IGS) using a global tracking network of around 150 stations, as well as precise orbit and satellite clock models determined by a combination of global analysis centres. The results show that the averaging technique is vulnerable to unmodelled errors in the satellite clock offsets from system time, leading to receiver CSE errors in the region of 12 ns (3.7 m), this value being largely driven by the satellite CSE errors. The global network approach is capable of delivering CSE errors at the level of 1.5 ns (46 cm) depending on the number of parameters in the linearised model. The International GNSS Service (IGS) receiver clock estimates were used as a truth model for comparative assessment.