室内定位技术与应用综述

近年来,随着基于位置服务日益增大的需求,以及基于卫星定位的全球导航卫星系统(GNSS)无法在室内定位的问题,针对复杂室内场景的室内定位技术发展迅速,逐步在各行各业中发挥作用,从各个方面影响着人们的日常生活。首先对目前主流的室内定位技术分类体系、定位原理和方法进行了详细介绍,然后对国内外室内定位技术的研究现状进行了分析和对比,最后对室内定位技术的应用和难点进行了总结。     

“北斗+5G”联合定位与误差校正技术

在边坡、城市峡谷、高架等复杂的公路交通定位环境中,存在海量多样的定位需求与复杂的定位环境,北斗信号穿越建筑空间时强度被削弱,产生严重的信号反射和衍射,使得北斗卫星信号难以到达和有效使用,系统可用率下降,无法提供可靠的定位服务。结合第五代移动通信网络（5G）系统高密度部署的特点,提出了一种北斗+5G联合定位模型以及基于最小二乘残差Helmert后验加权的误差校正方法。在复杂公路交通环境中,可以改善可见卫星数少的问题,优化卫星的几何构型,提高用户终端定位精度,能够为用户终端提供高精度、全天候、连续、实时的定位服务。实验表明,北斗+5G联合定位模型能够大幅提升复杂公路交通环境下的定位性能。     

北斗三号系统PPP-B2b信号定位服务模型及性能分析

给出了PPP-B2b信号定位的观测模型和随机模型,详细阐述了PPP-B2b增强改正模型和参数估计模型,并进行了静态和动态定位实验。结果表明：对于单系统,在30min的收敛时间内,北斗三号定位精度可以达到水平0.118m(静态)、0.176m(动态),高程0.208m(静态)、0.423m(动态)以内,GPS定位精度可以达到水平0.113m(静态)、0.163m(动态),高程0.206m(静态)、0.377m(动态)以内;对于北斗三号/GPS双系统,在20min的收敛时间内,定位精度可以达到水平0.092m(静态)、0.122m(动态),高程0.158m(静态)、0.312m(动态)以内。无论是收敛性还是定位精度,均能满足北斗三号精密单点定位服务指标的要求。     

高动态信号模拟器中的多普勒模拟算法

 为了测试卫星定位系统接收机的性能,须用信号模拟器来模拟各种条件下真实的卫星发射信号。卫星信号模拟器由软件、硬件和上位机三部分组成。系统主要包含目标运动轨迹计算、误差计算、导航电文生成及信号调制发射等功能模块。中频信号处理中的多普勒频移模拟是高动态卫星信号模拟器要解决的一项关键技术。为此,提出了一种全相参的多普勒模拟算法,基于真实的高动态运动模型解算出伪码和载波的频率字,在现场可编程门阵列（FPGA）中通过数控振荡器(NCO)设计产生真实的动态卫星信号。通过实际测试并与理论数据进行了比对验证,模拟出的动态特性与真实卫星信号的多普勒特性一致。     

Analysis of GNSS clock prediction performance with different interrupt intervals and application to real-time kinematic precise point positioning

Continuous and timely real-time satellite orbit and clock products are mandatory for real-time precise point positioning (RT-PPP). Real-time high-precision satellite orbit and clock products should be predicted within a short time in case of communication delay or connection breakdown in practical applications. For prediction, historical data describing the characteristics of the real-time orbit and clock can be used as the basis for performing the prediction. When historical data are scarce, it is difficult for many existing models to perform precise predictions. In this paper, a linear regression model is used to predict clock products. Seven-day GeoForschungsZentrum (GFZ) final clock products sampled at 30 s are used to analyze the characteristics of GNSS clocks. It is shown that the linear regression model can be used as the prediction model for the satellite clock products. In addition, the accuracy of the clock prediction for different satellites are analyzed using historical data with different periods (such as 2 and 10 epochs). Experimental results show that the accuracy of the clock with the linear regression prediction model using historical data with 10 epochs is 1.0 ns within 900 s. This is higher accuracy than that achieved using historical data of 2 epochs. Finally, the performance analysis for real-time kinematic precise point positioning (PPP) is provided using GFZ final clock prediction results and state space representation (SSR) clock prediction results when communication delay or connection breakdown occur. Experimental results show that the positioning accuracy without prediction is better than that with prediction in general, whether using the final clock product or the SSR clock product. For the final clock product, the positioning accuracy in the north (N), east (E), and up (U) directions is better than 10.0 cm with all visible GNSS satellites with prediction. In comparison, the 3D positioning accuracy of N, E, and U directions with visible GNSS satellites whose prediction accuracy is better than 0.1 ns using historical data of 10 epochs is improved from 15.0 cm to 7.0 cm. For the SSR clock product, the positioning accuracy of N, E, and U directions is better than 12.0 cm with visible GNSS satellites with prediction. In comparison, the 3D positioning accuracy of N, E, and U directions with visible GNSS satellites whose prediction accuracy is better than 0.1 ns using historical data of 10 epochs is improved from 12.0 cm to 9.0 cm.     

基于低轨稀疏星座的蓝绿激光对潜定位研究

潜艇只在必要时刻才浮出水面，对实时通信和导航定位造成极大制约。蓝绿激光具有深水穿透性高、衰减系数低等优势，已在机载和星载平台对潜艇通信中得到验证。借鉴GNSS导航信号产生原理，结合蓝绿激光通信测距一体化与低轨卫星自身精密定轨，提出了基于蓝绿激光通信的低轨卫星对潜定位算法。通过在激光通信中增加载波相位调制，实现潜艇激光接收器的伪距测量，联合其高程测量信息实现水下定位。以一带一路海域，特别是中国南海区域为服务对象，优化星座参数设计了3颗卫星组成的低轨稀疏星座。潜艇在星座覆盖区域内保持静态，间隔1~3min完成至少两次通信测距和导航电文接收，联合两组观测数据、精密星历及高程测量信息进行定位解算。仿真结果显示，在卫星过境期间，考虑卫星定轨精度，激光在空气、水下传播误差等因素，潜艇可在水下实现X、Z方向定位误差优于100m，Y方向误差约100~150m的高精度定位，对提升潜艇的战场作战能力具有意义。     

Correction model of BDS satellite-induced code bias and its impact on precise point positioning

There are code biases on the pseudo-range observations of the Beidou Navigation Satellite System (BDS) that range in size from several decimeters to larger than one meter. These biases can be divided into two categories, which are the code biases in the pseudo-range observations of Inclined Geo-Synchronous Orbit (IGSO) satellites and Medium Earth Orbit (MEO) satellites and the code biases in the pseudo-range observations of Geosynchronous Earth Orbit (GEO) satellites. In view of the code bias of the IGSO/MEO satellites, the code bias correction model is established using the weighted least square curve fitting method. After the correction, the code biases of the IGSO and MEO satellites are clearly mitigated. A methodology of correcting GEO code bias is proposed based on the empirical mode decomposition (EMD)-wavelet transform (WT) coupled model. The accuracies of the GEO multipath combination of the B1, B2 and B3 frequencies are improved by 39.9%, 17.9%, and 29.4%, respectively. Based on the corrections above, the ten days observations of three Multi-GNSS Experiment (MGEX) stations are processed. The results indicate that the convergence time of the precise point positioning (PPP) can be improved remarkably by applying a code bias. The mean convergence time can be improved by 14.67% after the IGSO/MEO code bias correction. By applying the GEO code bias, the mean convergence time can be further improved by 17.42%.     

Towards high accuracy GNSS real-time positioning with smartphones

The possibility to access undifferenced and uncombined Global Navigation Satellite System (GNSS) measurements on smart devices with an Android operating system allows us to manage pseudorange and carrier-phase measurements to increase the accuracy of real-time positioning. The goal is to perform real-time kinematic network positioning with smartphones, evaluating the positioning accuracy regarding an external mass-market device. The positioning of Samsung Galaxy S8+ and Huawei P10 plus smartphones was performed using a dedicated tool developed by the authors, considering a continuous operating reference station (CORS) network with a mean inter-station distance of about 50?km. The same positioning technique was also applied to an external GNSS low-cost single-frequency receiver (u-blox EVK-M8T) to compare performance between the receiver and antenna embedded in the previous smartphones and this low-cost receiver coupled with a mass-market antenna (Garmin GA38). Attention was also focused on the phase ambiguity resolution, that it is still a challenging aspect for mass-market devices: even if the two smartphones provide slightly different results, the accuracy obtainable today is greater than 60?cm with a precision of few centimetres in real-time, if a CORS network is available. For real-time applications using portable devices, decimetre-level accuracy is sufficient for many applications, such as rapid mapping and search and rescue activities: these results will open new frontiers in terms of real-time positioning with portable low-cost devices.     

Performance assessment of real-time multi-GNSS integrated PPP with uncombined and ionospheric-free combined observables

For precise position services, the real-time precise point positioning (PPP) is a promising technology. The real-time PPP performance is expected to be improved by multi-system combination. The performance of real-time multi-system PPP needs to be periodically investigated, with the increasing number of available satellites and the continuously improved quality of real-time precise products of satellite clocks and orbits. In this study, a comprehensive performance assessment is conducted for the four-system integrated real-time PPP (FSIRT-PPP) with GPS, BDS, Galileo and GLONASS in both static and kinematic modes. The datasets from 118 stations spanning approximately a month are used for analysis, and the real-time stream CLK93 is employed. The superior performance of FSIRT-PPP is validated by comparing with the results of GPS/BDS, GPS/Galileo, GPS/GLONASS, GPS-only, BDS-only, Galileo-only and GLONASS-only cases. The FSIRT-PPP using ionospheric-free (IF) combined observables can achieve a convergence time of 10.9, 4.8 and 11.8 min and a positioning accuracy of 0.4, 0.5 and 0.7 cm in the static mode in the east, north and up directions, respectively, while the derived statistic is 15.4, 7.0 and 16.4 min, and 1.6, 1.2 and 3.4 cm in the kinematic mode in the three directions, respectively. Moreover, we also compare the position solutions of real-time PPP adopting IF combined and uncombined (UC) observables, and prove the mathematical equivalence between the two PPP models in the converged stage, provided that there are no external ionospheric corrections or constraints given to the estimated ionospheric delays in the UC model. The difference between the fully converged positioning accuracy of IF-based and UC-based real-time PPP is marginal, but the UC-based real-time PPP has longer convergence time due to the influence of the significant unmodeled time-varying errors in the real-time precise products as well as the different parameterization between them. For completeness, the real-time kinematic PPP results in harsh environments and the post-processed PPP results are also presented.     

Fault detection and isolation in GPS receiver autonomous integrity monitoring based on chaos particle swarm optimization-particle filter algorithm

The receiver autonomous integrity monitoring (RAIM) is one of the most important parts in an avionic navigation system. Two problems need to be addressed to improve this system, namely, the degeneracy phenomenon and lack of samples for the standard particle filter (PF). However, the number of samples cannot adequately express the real distribution of the probability density function (i.e., sample impoverishment). This study presents a GPS receiver autonomous integrity monitoring (RAIM) method based on a chaos particle swarm optimization particle filter (CPSO-PF) algorithm with a log likelihood ratio. The chaos sequence generates a set of chaotic variables, which are mapped to the interval of optimization variables to improve particle quality. This chaos perturbation overcomes the potential for the search to become trapped in a local optimum in the particle swarm optimization (PSO) algorithm. Test statistics are configured based on a likelihood ratio, and satellite fault detection is then conducted by checking the consistency between the state estimate of the main PF and those of the auxiliary PFs. Based on GPS data, the experimental results demonstrate that the proposed algorithm can effectively detect and isolate satellite faults under conditions of non-Gaussian measurement noise. Moreover, the performance of the proposed novel method is better than that of RAIM based on the PF or PSO-PF algorithm.