双线程滑动窗口多系统GNSS超快精密定轨实现及评估

全球导航卫星系统（GNSS）超快精密定轨为GNSS实时应用提供了高精度空间基准。基于天地协同定位、导航与授时（PNT）网络服务中心实现了四系统GNSS卫星超快精密定轨,并对定轨结果进行精度评价。介绍了天地协同PNT网络的概念内涵以及网络服务中心部署的超快精密定轨软件架构和详细功能,并针对实时应用需求提出了一种双线程滑动窗口超快精密定轨策略。最后利用重叠弧段比较、与外部轨道产品比较以及卫星激光测距（SLR）检核3种方式对定轨结果进行了精度评价。结果表明,与武汉大学分析中心的最终事后精密轨道产品相比,四系统GNSS MEO卫星预报6 h弧段的径向均方根（RMS）误差整体在2~5 cm水平,BDS2 IGSO卫星最小一维RMS误差在10~15 cm水平;GPS和Galileo卫星的SLR检核残差均值在1~3 cm水平,标准差在3~6 cm水平,能够满足后续厘米级实时应用对空间基准的精度需求。     

Online INS/GPS integration with a radial basis function neural network

Most of the present navigation systems rely on Kalman filtering to fuse data from global positioning system (GPS) and the inertial navigation system (INS). In general, INS/GPS integration provides reliable navigation solutions by overcoming each of their shortcomings, including signal blockage for GPS and growth of position errors with time for INS. Present Kalman filtering INS/GPS integration techniques have some inadequacies related to the stochastic error models of inertial sensors, immunity to noise, and observability. This paper aims to introduce a multi-sensor system integration approach for fusing data from INS and GPS utilizing artificial neural networks (ANN). A multi-layer perceptron ANN has been recently suggested to fuse data from INS and differential GPS (DGPS). Although being able to improve the positioning accuracy, the complexity associated with both the architecture of multi-layer perceptron networks and its online training algorithms limit the real-time capabilities of this technique. This article, therefore, suggests the use of an alternative ANN architecture. This architecture is based on radial basis function (RBF) neural networks, which generally have simpler architecture and faster training procedures than multi-layer perceptron networks. The INS and GPS data are first processed using wavelet multi-resolution analysis (WRMA) before being applied to the RBF network. The WMRA is used to compare the INS and GPS position outputs at different resolution levels. The RBF-ANN module is then trained to predict the INS position errors and provide accurate positioning of the moving platform. Field-test results have demonstrated that substantial improvement in INS/GPS positioning accuracy could be obtained by applying the combined WRMA and RBF-ANN modules.     

Unmanned space vehicle navigation by GPS

In this paper, flight-path deviation in the navigation of unmanned space vehicles by global positioning system (GPS) is analyzed. A new method to calculate flight-path deviation by means of coordinate transforming is presented and the software of navigation and control is designed. This software is practical and effective for navigation by GPS with some characteristics including high-speed, high accuracy, real-time positioning and the use of digital mapping technique     

GPS/BDS组合定位精度分析

随着定位技术的不断发展及多系统导航定位技术的逐步推广,多系统组合导航定位已经成为了GNSS导航定位领域中的主要发展趋势。主要阐述了GPS/BDS组合相对定位的观测方程和数学模型,并根据实测数据对比分析,从卫星可见性、精度因子、定位精度和均方根误差等方面对GPS、BDS及GPS/BDS组合定位系统的定位性能、定位精度进行了比较。研究结果表明,较单一的GPS和BDS系统定位,采用GPS/BDS组合定位可有效提高卫星可见数目和DOP值,且稳定性更好。GPS/BDS组合定位的定位精度也明显优于单一系统,这对GNSS高精度导航定位具有重要的参考价值。     

基于UWB/SINS组合的行人导航研究

在特殊环境下全球定位系统(GPS)信号强度被严重削弱,此时基于GPS技术的导航设备将受到严重影响。针对不依赖GPS的行人导航定位需求,提出了一种基于微机电捷联惯导系统(SINS)与超宽带(UWB)定位系统相结合的行人导航方法。该系统由捷联惯导系统与超宽带定位系统组成,行人导航算法在传统的捷联算法的基础上引入了零速修正技术用于检测零速时刻,并使用阈值法剔除了超宽带错误信息,通过联邦Kalman滤波融合了零速、位置和航向信息,并对系统速度、位置、航向进行了校正。行人导航实验表明,该方法能够提升系统定位精度,并进一步加强系统的稳定性与可靠性。     

GPS／GLONASS共用PDOP研究

对全球卫星定位系统的DOP因子进行了分析。对GPS/GLONASS共用系统的可用性和PDOP因子进行了理论分析和软件仿真,对星座的定位特性进行了评估。分析结果表明,GPS/GLONASS共用系统相对于单一的GPS系统在可用性和PDOP因子方面都有很大的改善,从而可以进一步改善定位精度,这就为GPS/GLONASS组合导航的进一步研究和应用奠定了基础。     

低成本多传感器组合导航系统在小型无人机自主飞行中的研究与应用

为了满足小型无人机自主控制系统对导航系统性能的要求,研究低成本的基于微机电系统的捷联惯性导航系统(MEMS-SINS)/全球定位系统(GPS)/磁强计组合导航系统。提出一种利用磁强计辅助MEMS-SINS的静基座初始姿态确定方法,采用四元数误差模型对MEMS-SINS/GPS/磁强计组合导航系统进行信息融合的建模,采用基于正交三角(QR)分解的平方根无色卡尔曼滤波(UKF)非线性估计方法对组合导航系统进行数据融合,克服由于计算机舍入误差引起的状态协方差阵的计算值失去非负定性甚至对称性,通过小型无人机的自主飞行试验,证实MEMS-SINS/GPS/磁强计组合导航算法满足小型无人机自主控制系统的要求。     

一种适用于跑步状态的惯性/零速/GPS室内外无缝组合导航定位方法

目前,行人导航定位技术已经深入社会的众多领域,受到诸多学者的广泛关注。针对行人跑步状态,研究了一种惯性/零速/GPS室内外无缝组合导航定位方法。首先提出了可靠的、适用于行人跑步零速检测的方法,有效提高了在行人跑步状态下的零速检测的准确性。针对GPS信号容易受到高楼、高架等环境的干扰及在室内容易完全丢失的特点,提出了基于BP神经网络的GPS可用信号筛选方法,提高了GPS信息的可靠性与精准性。在此基础上,研究了基于可变量测的Kalman滤波器,实现了惯性/零速/GPS信息的有效融合,显著提高了在行人跑步状态下的导航定位精度。试验结果表明,所提出的这种适用于跑步状态的惯性/零速/GPS室内外无缝组合导航定位方法的平均定位误差可减小到行人跑步总里程的1%以内。     

Model-based robust estimation and fault detection for MEMS-INS/GPS integrated navigation systems

In micro-electro-mechanical system based inertial navigation system（MEMS-INS）/global position system（GPS） integrated navigation systems, there exist unknown disturbances and abnormal measurements. In order to obtain high estimation accuracy and enhance detection sensitivity to faults in measurements, this paper deals with the problem of model-based robust estimation（RE） and fault detection（FD）. A filter gain matrix and a post-filter are designed to obtain a RE and FD algorithm with current measurements, which is different from most of the existing priori filters using measurements in one-step delay. With the designed filter gain matrix, the H-infinity norm of the transfer function from noise inputs to estimation error outputs is limited within a certain range; with the designed post-filter, the residual signal is robust to disturbances but sensitive to faults. Therefore, the algorithm can guarantee small estimation errors in the presence of disturbances and have high sensitivity to faults. The proposed method is evaluated in an integrated navigation system, and the simulation results show that it is more effective in position estimation and fault signal detection than priori RE and FD algorithms.     

Preliminary Evaluation of GPS Performance for Low-Cost General Aviation

Preliminary results of a simulation effort to evaluate the requirements and feasibility of the global positioning system (GPS) as a civil air navigation system are presented. Evaluation is made of GPS requirements, from operational considerations, such as application to nonprecision approaches. The conceptual low-cost GPS receiver simulated here does not correct for the ionospheric or trophospheric delay, is sequential in nature, tracks only four satellites, and is not mechanized to make independent range rate measurements based on the Doppler shift of the GPS carrier frequency. The proposed GPS system has significantly different performance characteristics from the presently used VHF omnidirectional range (VOR) solidus distance-measuring equipment (DME) system. The GPS is a low signal level system and many have a relatively slow data rate due to the low-cost sequential receiver design. The results indicate that although the conceptual low-cost GPS receiver/ navigator is potentially more accurate than a VOR, the accuracy may degrade during aircraft turns and satellite shielding periods.     

基于火箭橇的北斗动态定位精度鉴定方法

介绍了几种现有的以GPS/北斗为主要代表的卫星导航系统的动态定位精度 鉴定方法,分析了这几种方法在模拟实际使用环境、鉴定精度等方面的优缺点,提出了 一种基于火箭橇试验平台的北斗导航定位系统动态定位精度鉴定方法。该方法能够很好 地模拟北斗导航定位系统实际工作环境（速度、加速度、振动和天线角度等）,解决高 动态、高精度北斗导航定位系统动态定位精度鉴定问题,并对该方法的原理和实施方法 作了详细的论述,最后分析了该方法的不确定度及误差,并提出了改进措施。     

Intelligent SINS/RDSS Integrated Algorithms for Land Vehicle Navigation

This is a discussion of the design of strap-down inertial navigation systems (SINS) and radio determination satellite service (RDSS) integrated navigation algorithms. The research aims at testing the effectiveness of artificial intelligence (AI)-aided Kalman filtering (KF) approaches for land vehicle applications. A back-propagation neural network (BPNN)-aided K*F algorithm and a fuzzy inference-based KF algorithm are presented in order to overcome the time delay of RDSS positioning provided by a double-star positioning system in China. Traditional KF causes biased solutions, and indeed, leads to filter instability easily since the time delay of RDSS positioning, in an active mode, is hard to be modeled and sometimes suffers from RDSS outages. Therefore, a fuzzy inference is used to correct the variance matrix of KE measurement noises adaptively; and a trained BPNN corrects the outputs of the Kalman filter. The algorithms proposed herein have been verified on real SINSIRDSS data. collected in land vehicle tests and are compared with other approaches. The results demonstrate that fuzzy inference-based KF algorithms improve the positioning accuracy to over 40 % better than KF algorithms, and BPNN-aided KF algorithms have the same precision as GPS which is the reference station In dynamic experiments without RDSS outages. The test results with RDSS outages indicate that the fuzzy inference-based KF is feasible but with positioning errors of hundreds of meters, so the BPNN-aided KF is designed to efficiently compensate for RDSS outages and improve system performance.     

改进概率关联算法在组合导航系统中的应用研究

针对组合导航系统中子系统提供的量测信息相互之间关联性不足的问题,在组合导航系统中引入改进概率关联算法,通过改进的概率关联算法将这些导航信息按一定关系联系起来并进行融合计算。首先通过推导短时间概率关联算法求解惯性导航系统(INS)得到信息的可信概率,并引入掩模算子对全球定位系统(GPS)信息进行精度判断;然后,推导出长时间概率关联算法对组合导航系统信息进行融合;最后,建立修正算法并利用长时间概率关联算法得到的信息对惯性导航系统进行误差修正。仿真结果表明,这一改进的概率关联算法可以有效判断GPS信息精度并提高组合导航系统的导航精度。     

基于计算机视觉/GPS/MG姿态测量的盲人行走组合导航方法研究

电子导盲辅助装置(ETA)是解决盲人出行困难的重要手段,而导航是ETA的关键技术.现有的ETA主要用GPS来定位定向,但在城市环境中经常存在GPS信号遮挡导致导航信息丢失的问题.针对该问题,利用视觉导航短时间内定位精度高,输出连续的优点以及 MG(Magnetic Gravity)姿态测量可补偿姿态积累误差的优点,提出一种基于视觉、GPS和MG姿态测量的盲人行走组合导航算法.该方法构建系统误差模型并以Kalman滤波为框架.仿真和实验结果表明,提出的组合导航算法准确度优于单独的导航算法,满足盲人户外安全出行导航的需求.     

Evaluation of GPS Ionospheric Time-Delay Model

For single-frequency global positioning system (GPS) users,uncompensated ionospheric GPS-signal time delay is the largestsource of range-measurement error, contributing as much as 100 m.To improve performance for these users, a numeric model of theionospheric range error was incorporated into the GPS system. Thispaper presents an assessment of that model in which actualionospheric time-delay values as measured by GPS dual-frequencyreceivers were compared with model values computed at the sametime points. Comparison was made over a broad range of conditionswith dependency of model accuracy on several of the modelparameters. It appears that the model leads to an overall reductionin rms range measurement error of 60 percent.     

Multi-sensor optimal data fusion for INS/GPS/SAR integrated navigation system

INS/GPS/SAR integrated navigation system represents the trend of next generation navigation systems with the high performance of independence, high precision and reliability. This paper presents a new multi-sensor data fusion methodology for INS/GPS/SAR integrated navigation systems. This methodology combines local decentralized fusion with global optimal fusion to enhance the accuracy and reliability of integrated navigation systems. A decentralized estimation fusion method is established for individual integrations of GPS and SAR into INS to obtain the local optimal state estimations in a parallel manner. A global optimal estimation fusion theory is studied to fuse the local optimal estimations for generating the global optimal state estimation of INS/GPS/SAR integrated navigation systems. The global data fusion features a method of variance upper finiteness and a method of variance upper bound to ensure that the global optimal state estimation can be achieved under a general condition. Experimental results demonstrate that INS/GPS/SAR integrated navigation systems achieved by using the proposed methodology have a better performance than INS/GPS integrated systems.     

Carrier phase navigation architecture for shipboard relative GPS

Carrier phase differential GPS (DGPS) navigation architectures and algorithms for automatic shipboard landing of aircraft are described. Processing methodologies are defined to provide high integrity carrier phase cycle estimation and positioning by optimally exploiting the complementary benefits of measurement filtering and satellite geometric redundancy for the terminal navigation problem. Navigation performance sensitivity to the standard deviations of raw carrier and code phase measurement errors, measurement error correlation times, and the filtering duration is quantified. Necessary conditions to ensure acceptable terminal navigation availability are specifically defined.     

Basic performance of BeiDou-2 navigation satellite system used in LEO satellites precise orbit determination

The visibility for low earth orbit（LEO） satellites provided by the BeiDou-2 system is analyzed and compared with the global positioning system（GPS）. In addition, the spaceborne receivers＇ observations are simulated by the BeiDou satellites broadcast ephemeris and LEO satellites orbits. The precise orbit determination（POD） results show that the along-track component accuracy is much better over the service area than the non-service area, while the accuracy of the other two directions keeps at the same level over different areas. However, the 3-dimensional（3D） accuracy over the two areas shows almost no difference. Only taking into consideration the observation noise and navigation satellite ephemeris errors, the 3D accuracy of the POD is about30 cm. As for the precise relative orbit determination（PROD）, the 3D accuracy is much better over the eastern hemisphere than that of the western hemisphere. The baseline length accuracy is 3.4 mm over the service area, and it is still better than 1 cm over the non-service area. This paper demonstrates that the BeiDou regional constellation could provide global service to LEO satellites for the POD and the PROD. Finally, the benefit of geostationary earth orbit（GEO） satellites is illustrated for POD.     

基于低轨通信星座的导航增强技术发展概述

在我国北斗三号卫星导航系统全面完成组网建设的背景下,世界卫星导航步入新时代。各卫星导航大国均瞄准更高服务精度、更加多样功能、更加可靠服务,正在着手开展新一代系统建设和技术迭代。随着各国对于大型低轨通信星座的积极开发与广泛部署,应用低轨卫星技术实现导航增强与PNT系统备份能力,因其易与GNSS协同,具有提高全球自主导航精度、拓展全球卫星导航应用市场的巨大潜力而成为研究热点。面向低轨导航增强技术,首先总结了低轨卫星的最新态势,梳理了卫星导航增强服务模式,并详细分析了低轨通信星座导航精度增强及导航信号增强两方面的技术动向。在此基础上,重点针对导航增强频率的兼容互操作、通信/导航信号一体化设计、高动态导航增强信号捕获与跟踪等方面,对低轨卫星导航增强体系未来的发展机遇以及面临的技术挑战进行了展望。此外,还基于美国铱星系统实收采集信号开展了定位服务性能试验分析,结果表明600个历元内收敛定位精度优于100m,相关分析成果可为我国低轨导航增强建设提供参考和借鉴。     

Use of MOBITEX wireless wide area networks as a solution toland-based positioning and navigation

The emergence of land-based positioning and navigation systems is the direct result of advancements in technologies relating to geographic information, wireless data communication, and navigation. The increasing demand for these systems has stimulated their rapid development. This paper identifies the wide variety of land-based positioning and navigation systems and classifies them into five groups. The basic system elements that are required in all land-based positioning and navigation systems are also discussed. A proposed system infrastructure that supports the five types of land-based positioning and navigation systems is described. The specific technologies integrated in this proposed infrastructure include the Global Positioning System (GPS), differential GPS, and the MOBITEX wireless wide area packet data networks. Real-time wireless mobile data communication is a key component of any land-based positioning and navigation system. Finally, the evaluation criteria necessary for field testing a pilot land-based positioning and navigation system are presented. This pilot system is used to determine the feasibility and effectiveness of the proposed system design