一种基于加表零偏稳定性的GNSS/SINS组合导航异常探测方法

在地面车载组合导航中,全球导航卫星系统（global navigation satellite system,GNSS）的观测值容易受地面复杂环境的干扰,导致其定位结果出现异常,严重影响GNSS/捷联惯性导航系统（strap-down inertial navigation system,SINS）组合的滤波解算。从惯导系统误差特性的角度,研究了一种基于加表零偏稳定性的组合导航异常探测新方法。该方法从加表零偏解算的异常来发现GNSS位置、速度等观测值中的粗差,并采取剔除和降权的抗差方法抵御粗差影响。通过一组车载数据的分析表明,观测粗差对加表零偏解算的影响十分显著,以此为判别条件能够准确地发现观测粗差。采用该方法后,位置误差、速度误差和姿态误差的均方根分别减小了70.8%、87.9%和77.7%,显著提高了组合导航的解算精度和鲁棒性,为组合导航数据的抗差处理提供了一种新思路。     

BDS RTK／MEMS-INS组合数学模型研究与性能分析

卫星导航系统和惯性导航系统（INS）具有极强的互补性,两者组合能有效提高导航定位结果的可用性、连续性和可靠性. 随着北斗卫星导航系统（BDS）的快速发展和低成本惯导元件（IMU）性能的不断提高,进行基于BDS和低成本IMU的组合导航系统相关理论和技术研究具有很强的研究意义和实用价值. 本文首先对BDS RTK／M-EMS INS组合理论模型进行推导,并利用实测车载数据对组合系统的性能进行分析. 实验结果表明,在BDS中引入低成本IMU,可以在不损失定位精度的同时有效改善测速精度. 组合后在车载动态中定位精度影响为mm级,而速度误差改善在北、东、地方向达到了75.8％、79.5％、66.7％. 此外,在BDS+INS紧组合中使用双频数据可以改善测速定姿精度,速度误差改善为18.2％、33.3％、33.3％,姿态误差改善为41.1％、26.7％、59.0％.      

Improved decentralized multi-sensor navigation system for airborne applications

The integration of Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) technologies is a very useful navigation option for high-accuracy positioning in many applications. However, its performance is still limited by GNSS satellite availability and satellite geometry. To address such limitations, a non-GNSS-based positioning technology known as “Locata” is used to augment a standard GNSS/INS system. The conventional methods for multi-sensor integration can be classified as being either in the form of centralized Kalman filtering (CKF), or decentralized Kalman filtering. However, these two filtering architectures are not always ideal for real-world applications. To satisfy both accuracy and reliability requirements, these three integration algorithms—CKF, federated Kalman filtering (FKF) and an improved decentralized filtering, known as global optimal filtering (GOF)—are investigated. In principle, the GOF is derived from more information resources than the CKF and FKF algorithms. These three algorithms are implemented in a GPS/Locata/INS integrated navigation system and evaluated using data obtained from a flight test. The experimental results show that the position, velocity and attitude solution derived from the GOF-based system indicate improvements of 30, 18.4 and 20.8% over the CKF- and FKF-based systems, respectively.     

改进的GNSS/SINS组合导航系统自适应滤波算法

GNSS/SINS(global navigation satellite system/strapdown inertial navigation system)组合导航系统已得到广泛的应用与研究,当处于复杂环境时,GNSS输出容易出现误差均方差突变、误差均方差缓变、硬故障和软故障4种现象,进而影响组合导航系统滤波精度及载体的导航安全。为了解决上述问题,提出了一种改进的GNSS/SINS组合导航系统自适应滤波算法。首先,利用滤波过程中的观测异常检验统计量与滤波器门限值构建观测因子,然后,将变分贝叶斯原理与抗野值滤波方法结合,设计了改进的组合导航系统自适应滤波算法。仿真实验表明,相较于传统算法,当GNSS输出误差均方差发生变化时,所提算法可将位置精度及速度精度提高11.8%及13.7%;在GNSS输出发生硬故障时,所提算法可将位置精度及速度精度提高70.8%及69.6%。实验结果表明,所提算法具有较强的自适应性,可提升复杂环境下组合导航系统的精度和连续可用性。     

Using Allan variance to improve stochastic modeling for accurate GNSS/INS integrated navigation

MEMS-based integrated system of a global navigation satellite system (GNSS) and an inertial navigation system (INS) has been widely used in various navigation applications. However, such integration encounters some major limitations. On the one hand, the noisy MEMS-based INS undermines the accuracy with time during the frequently occurring GNSS outages caused by signal blockage or attenuation in certain situations such as urban canyon, tunnels, and high trees. On the other hand, the model mismatch between actual GNSS error and the assumed one would also degrade the obtained accuracy even with continuous GNSS aiding. To improve the overall performance for GNSS/MEMS-INS, better error models can be obtained using Allan variance (AV) analysis technique for modeling inertial sensor errors instead of the commonly recommended auto-regressive processes, and on the other hand, the measurement update in Kalman filter is improved using innovation filtering and AV calculation. The performance of each method and the combined algorithm is evaluated by a field test with either differential GNSS (DGNSS) or single-point positioning (SPP) as external aid. In addition to the considerable navigation enhancement brought by each method, the experimental results show the combined algorithm accomplishes overall accuracy improvements by about 18% (position), 8% (velocity), and 38% (attitude) for integration with DGNSS, and by about 15% (position), 75% (velocity), and 77% (attitude) for that with SPP, compared with corresponding traditional counterparts.     

智能手机多频多系统实时动态的定位性能分析

随着位置服务的发展,人们对定位精度的需求不断提升. 目前智能手机定位主要依赖于全球卫星导航系统(GNSS)芯片所提供的芯片解,其精度仅为米级. 2016年,谷歌宣布允许开发者获取手机GNSS原始观测数据,为研究手机GNSS高精度定位算法提供了支持. 为探索智能手机多频多系统实时动态(RTK)的定位精度和可靠性,文中基于华为P40智能手机开展了静态和动态环境下的多频多系统RTK的定位性能分析. 结果表明:在静态环境下,智能手机多频多系统的RTK定位精度要优于芯片解,在东(E)、北(N)、天(U)三个方向的定位误差均方根(RMS)分别为0.20 m、0.39 m和0.31 m,比芯片解提高了57%、71%和75%;在动态环境下的定位精度依然能够达到分米级,相比于芯片解在E、N、U三个方向上的定位精度提高了37.84%、47.22%、53.68%.      

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。     

相位平滑伪距GNSS PPP/INS紧耦合算法

针对在导航实践中低成本MEMS使用传统紧耦合方法计算精度受到限制的问题,提出了一种采用载波相位平滑伪距GNSS PPP/INS紧耦合的算法。实验表明,使用相位平滑伪距的GNSS PPP/INS紧耦合方法后低精度的MEMS和GPS组合位置精度为dm级,速度精度为cm/s甚至mm/s,比传统C/A码紧耦合定位精度高,有较好的收敛性;其次当增加相位平滑的历元数后精度也相应提高。当出现GPS信号中断时,该方法能够加速中断以后滤波收敛的速度,将导航精度控制在中高精度惯导作业要求范围内。该方法节约了导航作业的设备成本,具有一定实际意义。     

Enhancement of the accuracy of single-epoch GPS positioning for long baselines by local ionospheric modelling

Single-epoch relative GPS positioning has many advantages, especially for monitoring dynamic targets. In this technique, errors occurring in previous epochs cannot affect the position accuracy at the current epoch, but careful processing is required, and resolving carrier phase ambiguities is essential. Statistical ambiguity resolution functions have been used to determine the best values of these ambiguities. The function inputs include as a minimum the known base station position, the approximate roving antenna “seed” position, and the dual-frequency carrier phase measurements from both receivers. We investigate different solutions to find the ambiguity function inputs that achieve the highest ambiguity resolution success rate. First, we address the rover seed position. A regionally filtered undifferenced pseudorange coordinate solution proves better than a double-differenced one. Multipath errors approximately repeat themselves every sidereal day in the case of static or quasi-static antennas; applying a sidereal filter to the pseudorange-derived positions mitigates their effects. Second, we address the relative carrier phase measurements, which for medium to long baselines are significantly affected by ionospheric propagation errors imperfectly removed during differencing. In addition to the International GNSS Service ionospheric model, we generate a local pseudorange-based ionospheric correction. Applying this correction improves the quality of the phase measurements, leading to more successful ambiguity resolution. Temporally smoothing the correction by means of a Kalman filter further improves the phase measurements. For baselines in the range 60–120 km, the mean absolute deviation of single-epoch coordinates improves to 10–20 cm, from 30–50 cm in the default case.     

陆地导航中GNSS/陀螺仪组合实时测姿方法

在陆地导航系统中使用GNSS/INS组合导航会增加系统成本,多天线GNSS测姿精度受基线长度影响,且存在的模糊度固定问题。本文提出仅利用一个陀螺仪和单天线GNSS组合来进行实时测姿。先由单天线GNSS计算姿态角3参数,航向角为陆地导航的关键参数,为此将陀螺信息与GNSS导出的航向角进行融合。分析了单天线测姿在载体静止或低速运动时精度很差的原因,提出了在组合滤波中进行解决的方案。推导了GNSS和陀螺信息融合的滤波模型,将陀螺仪信息作为状态模型的控制输入,以GNSS航向为滤波观测值。实验结果表明,GNSS/陀螺仪组合计算的航向角精度和可靠性相对GNSS测姿结果均有很大提升。     

四大GNSS广播星历精度评估与对比分析

分析了 目前广播星历精度评估中存在的问题,详细论述了广播星历精度评估过程中对精密星历进行天线相位中心改正的取值方法,提出了利用单颗星单日钟差均值作二次差对广播星历钟差的系统性偏差进行改正的方法.选取2019-09-01-2019-11-01 共计62天的多模 GNSS 实验(multi-GNSS experiment,...     

船载GNSS探测海洋水汽信息的影响因子分析

利用船载全球卫星导航系统（global navigation satellite system,GNSS）方式探测海洋水汽含量,可丰富海洋水汽观测量和观测密度。利用印度洋航次试验实测数据,基于精密单点定位技术对海洋上空可降水份探测的精度问题进行了研究,主要分析了GNSS高程与可降水份之间存在的耦合关系,标定了动态GNSS的高程精度,分析了不同算法对可降水份估值的影响。结果显示:①固定解与浮点解、多系统与单系统对可降水份估算的影响不大,而不同软件、不同卫星星历和钟差产品对可降水份估算的影响较大,量级为2~4 mm;②高程与可降水份之间存在耦合关系,经初步估算,高程的均方根误差每增加24mm,则可降水份估值的均方根误差相应增加约1mm;③惯性测量单元垂荡值与精密单点定位高程结果之间的相关系数高达99%,二者的互差优于30mm,满足动态GNSS海洋水汽估计对高程精度的要求。     

附加约束条件对GNSS/INS组合导航结果的影响分析

针对车载全球导航卫星系统/惯性导航系统（global navigation satellite system/inertial navigation system,GNSS/INS）组合导航中卫星信号中断,惯性导航系统单独导航误差积累较大的问题,提出了附加载体运动条件约束的卡尔曼（Kalman）滤波解算方法。通过利用载体固有的运动约束,包括近似高程约束、近似速度约束和近似姿态约束,减少载体自由度和模型参数;通过引入新的观测类型,增加观测冗余,可以加强Kalman滤波解,提高在GNSS信号中断时组合导航系统的定位精度,实现无缝导航。     

基于抗差EKF的GNSS/INS紧组合算法研究

提出了GNSS/INS紧组合导航的抗差EKF算法,采用21状态GNSS/INS紧组合状态方程,根据多余观测分量及预测残差统计构造抗差等价增益矩阵,建立抗差EKF算法,通过迭代给出GNSS/INS组合导航的抗差解,并开发GNSS/INS紧组合导航模拟平台,通过对观测值加入单粗差、多粗差及缓慢增长三类误差,测试本文算法对不同粗差的抑制能力。分析表明,抗差EKF可以将三类粗差抑制在相应观测值的残差中,达到削弱其对状态参数估计的影响。本文算例证明,抗差EKF算法可将导航解的误差精度从dm级提高为cm级甚至mm级,导航精度及可靠性得到明显提高。     

GNSS+INS组合定位在矿山无人驾驶卡车的应用

面向矿山无人驾驶卡车场景,针对GNSS定位不连续且容易被干扰、INS存在累计误差的缺点,本文提出了一种基于GNSS+INS组合的导航算法,该算法融合了两种算法的优点,提高了定位的精度和可靠性。分别将RTK算法和组合导航算法结果与开源软件RTKLIB和NovAtel板载输出结果对比。试验结果表明,本文算法在精度上与NovAtel板载输出结果基本持平,明显优于RTKLIB软件。本文算法平面和高程误差均值及STD均优于5 cm,姿态误差均值和STD优于1°,可以满足矿用无人驾驶卡车的定位精度需求。     

基于独立分量法的新疆GNSS时间序列共模误差分析CSCD

共模误差(CME)是区域连续全球卫星导航系统(GNSS)网中的主要误差来源之一.针对GNSS时间序列具有非高斯分布特征,基于二阶统计量的主成分分析(PCA)难以准确提取出CME分量问题,采用具有高阶统计量的独立分量分析(ICA)对CME进行提取.以2011—2018年新疆区域GNSS坐标时间序列为例,将PCA滤波效果进行对比验证,分析了CME对GNSS坐标时间序列的影响,并对CME序列进行周期分析.结果表明:前6个独立分量包含CME分量,这可能与卫星轨道、地表质量负荷和时钟误差有关,ICA滤波后东(N)、北(E)、天顶(U)三个方向的均方根(RMS)值分别降低31.83%、32.29%、35.49%,速度不确定度分别降低44.14%、38.49%、43.32%,各测站的周期项振幅较滤波前更一致,有效地剔除了CME,提高了坐标时间序列的精度.     

抗差估计在RTK／INS紧组合中的应用研究

针对动态环境下GNSS／INS导航定位结果常受粗差影响的问题,提出了一种基于抗差卡尔曼滤波的GPS／BDS双系统RTK／INS紧组合导航定位算法,根据方差膨胀模型,建立抗差卡尔曼算法,得到GNSS／INS紧组合抗差解,并通过两个不同区域的实测车载实验进行了算法验证. 实验结果表明:本方法相较于传统方法,在N、E、D三个方向的导航精度分别提高1.4～4.6 cm,0.7～9 cm,1.5～2 cm,模糊度固定成功率提高10.3％～25.6％,导航精度及可靠性得到显著提高,对动态环境下车载或自动驾驶等应用具有一定的理论参考和实用价值.      

An enhanced MEMS-INS/GNSS integrated system with fault detection and exclusion capability for land vehicle navigation in urban areas

We describe an enhanced quality control algorithm for the MEMS-INS/GNSS integrated navigation system. It aims to maintain the system’s reliability and availability during global navigation satellite system (GNSS) partial and complete data loss and disturbance, and hence to improve the system’s performance in urban environments with signal obstructions, tunnels, bridges, and signal reflections. To reduce the inertial navigation system (INS) error during GNSS outages, the stochastic model of the integration Kalman filter (KF) is informed by Allan variance analysis and the application of a non-holonomic constraint. A KF with a fault detection and exclusion capability is applied in the loosely and tightly coupled integration modes to reduce the adverse influence of abnormal GNSS data. In order to evaluate the performance of the proposed navigation system, road tests have been conducted in an urban area and the system’s reliability and integrity is discussed. The results demonstrate the effectiveness of different algorithms for reducing the growth of INS error.     

CNS+GNSS+INS船载高精度实时定位定姿算法改进研究

天文导航(CNS)、卫星导航(GNSS)和惯性导航(INS) 3种系统组合可提供高精度的定位定姿结果。实际工程中因INS长时间误差累积,以及系统硬件传输存在不可忽略的时间延迟,导致INS提供给CNS的预报粗姿态误差较大,恶劣海况下难以保障快速搜星,造成天文导航可靠性下降、姿态测量精度较低的问题。为此,本文提出了一种CNS+GNSS+INS高精度信息融合实时定位定姿框架,引入了等角速度外推措施,有效地解决了惯导信息延迟问题。通过高精度转台模拟恶劣海况下载体大角速度摇摆,验证了本文提出的改进算法的有效性。试验结果表明,该算法架构简单,性能可靠,显著提高了恶劣环境下星敏感器的快速、准确搜星能力,保障了三组合姿态测量的精度和可用性。     

Remote leveling of tide gauges using GNSS reflectometry: case study at Spring Bay,Australia

We further developed a new approach using GNSS reflectometry to determine the leveling connection between a tide gauge and a GNSS antenna. This approach includes the optimization of the unknown receiver bandwidth and the estimation of frequency changes in the signal-to-noise ratio (SNR) oscillation through an extended Kalman filter/smoother algorithm. We also corrected the geometric bending of the GNSS signals due to tropospheric refraction using local meteorological observations. Using 3 weeks of SNR data in Spring Bay, Australia, from a GNSS antenna placed sideways (i.e., ground plane orientated vertically and directed in azimuth toward the sea surface) to improve the SNR interference near the horizon, we obtained mean leveling differences of approximately 5 mm, with an RMS of approximately 3 cm level with respect to the nominal leveling from classical surveying techniques. SNR data from three different receiver manufacturers, coupled to the same antenna, provided similar leveling results. With a second antenna in the usual upright configuration, we obtained mean leveling differences of 1–2 cm and a RMS of about 10 cm. In the upright configuration, the leveling differences may include errors in the GNSS antenna phase center calibration, which are avoided in our technique but not in the classical surveying techniques. These results demonstrate the usefulness of the reflectometry technique to obtain precisely and remotely the leveling between a GNSS antenna and a tide gauge. In addition, this technique can be applied continuously, providing an independent and economical means to monitor the stability of the tide gauge zero.