Accuracy of iPhone Locations: A Comparison of Assisted GPS,WiFi and Cellular Positioning

The 3G iPhone was the first consumer device to provide a seamless integration of three positioning technologies: Assisted GPS (A‐GPS), WiFi positioning and cellular network positioning. This study presents an evaluation of the accuracy of locations obtained using these three positioning modes on the 3G iPhone. A‐GPS locations were validated using surveyed benchmarks and compared to a traditional low‐cost GPS receiver running simultaneously. WiFi and cellular positions for indoor locations were validated using high resolution orthophotography. Results indicate that A‐GPS locations obtained using the 3G iPhone are much less accurate than those from regular autonomous GPS units (average median error of 8 m for ten 20‐minute field tests) but appear sufficient for most Location Based Services (LBS). WiFi locations using the 3G iPhone are much less accurate (median error of 74 m for 58 observations) and fail to meet the published accuracy specifications. Positional errors in WiFi also reveal erratic spatial patterns resulting from the design of the calibration effort underlying the WiFi positioning system. Cellular positioning using the 3G iPhone is the least accurate positioning method (median error of 600 m for 64 observations), consistent with previous studies. Pros and cons of the three positioning technologies are presented in terms of coverage, accuracy and reliability, followed by a discussion of the implications for LBS using the 3G iPhone and similar mobile devices.     

Measured performance of the application of EGNOS in the road traffic sector

European Geostationary Navigation Overlay Service (EGNOS) is a satellite-based system developed to improve the performance of GPS in the European region. It not only enhances the estimated positioning accuracy but also provides an integrity solution. We assess the EGNOS performance through analysis of real measurements, performed in different road user environments. We investigate the use of the integrity concept in future Global Navigation Satellite System (GNSS)-based applications in the road environment, considering both suburban and dense urban areas. The analysis is motivated by the fact that there is an increasing number of road applications, such as billing system, transportation of dangerous goods, remote tracking of trucks and snow plows, fleet management and “pay as you go” car insurances, where the system liability has to be guaranteed. The scope of the analysis is to investigate to which extent the use of the integrity concept can be used for such purpose; the assessment is based on real measurement campaigns in representative environments, providing statistical results in terms of accuracy and integrity, and in a wider sense of the feasibility of the use of EGNOS for augmenting the reliability of GNSS positioning for road applications.     

A combined algorithm of improving INS error modeling and sensor measurements for accurate INS/GPS navigation

Although the integrated system of a differential global positioning system (DGPS) and an inertial navigation system (INS) had been widely used in many geodetic navigation applications, it has sometimes a major limitation. This limitation is associated with the frequent occurrence of DGPS outages caused by GPS signal blockages in certain situations (urban areas, high trees, tunnels, etc.). In the standard mechanization of INS/DGPS navigation, the DGPS is used for positioning while the INS is used for attitude determination. In case of GPS signal blockages, positioning is provided using the INS instead of the GPS until satellite signals are obtained again with sufficient accuracy. Since the INS has a very short-time accuracy, the accuracy of the provided INS navigation parameters during these periods decreases with time. However, the obtained accuracy in these cases is totally dependent on the INS error model and on the quality of the INS sensor data. Therefore, enhanced navigation parameters could be obtained during DGPS outages if better inertial error models are implemented and better quality inertial measurements are used. In this paper, it will be shown that better INS error models are obtained using autoregressive processes for modeling inertial sensor errors instead of Gauss–Markov processes that are implemented in most of the current inertial systems and, on the other hand, that the quality of inertial data is improved using wavelet multi-resolution techniques. The above two methods are discussed and then a combined algorithm of both techniques is applied. The performance of each method as well as of the combined algorithm is analyzed using land-vehicle INS/DGPS data with induced DGPS outage periods. In addition to the considerable navigation accuracy improvement obtained from each single method, the results showed that the combined algorithm is better than both methods by more than 30%.     

伪卫星增强GPS方法在变形监测中的应用研究

应用GPS对深开采的露天矿以及深山峡谷中的水库大坝进行变形监测,由于接收到的GPS卫星数目减少,导致GPS定位精度大大降低。采用伪卫星增强GPS的定位技术是解决这个问题的有效途径之一。提出GPS伪卫星组合测量新方法,建立组合观测量模型,开发减小伪卫星多路径效应的方法。基于实际的水电站观测数据分析伪卫星增强GPS提高定位精度的效果,给出GPS伪卫星组合定位的试验结果并验证所开发方法的有效性。     

Accuracy of iPhone Locations: A Comparison of Assisted GPS, WiFi and Cellular Positioning

The 3G iPhone was the first consumer device to provide a seamless integration of three positioning technologies: Assisted GPS (A-GPS), WiFi positioning and cellular network positioning. This study presents an evaluation of the accuracy of locations obtained using these three positioning modes on the 3G iPhone. A-GPS locations were validated using surveyed benchmarks and compared to a traditional low-cost GPS receiver running simultaneously. WiFi and cellular positions for indoor locations were validated using high resolution orthophotography. Results indicate that A-GPS locations obtained using the 3G iPhone are much less accurate than those from regular autonomous GPS units (average median error of 8 m for ten 20-minute field tests) but appear sufficient for most Location Based Services (LBS). WiFi locations using the 3G iPhone are much less accurate (median error of 74 m for 58 observations) and fail to meet the published accuracy specifications. Positional errors in WiFi also reveal erratic spatial patterns resulting from the design of the calibration effort underlying the WiFi positioning system. Cellular positioning using the 3G iPhone is the least accurate positioning method (median error of 600 m for 64 observations), consistent with previous studies. Pros and cons of the three positioning technologies are presented in terms of coverage, accuracy and reliability, followed by a discussion of the implications for LBS using the 3G iPhone and similar mobile devices.     

北斗/GPS组合定位方法

随着北斗卫星导航系统的逐渐完善,有关北斗系统定位的研究越来越深入,为了对比分析北斗系统和全球定位导航系统(GPS)定位的差异性,充分利用北斗地球静止轨道卫星(GEO)和倾斜地球同步轨道卫星(IGSO)高轨道卫星的特殊性,本文提出一种新的组合选星方法,选取卫星数较少且Position Dilution of Precision(PDOP)最小的北斗/GPS组合,分别对比分析北斗系统、GPS系统及其组合系统在楼顶开放环境和楼间恶劣环境下的定位效果。实验结果表明:北斗比GPS有更加稳定的定位效果,依据本文组合选星方法,利用少量卫星即可获得较好的定位精度。     

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。     

An integrated land vehicle navigation system based on context awareness

In the complex urban environments, land vehicle navigation purely relying on GNSS cannot satisfy user needs due to the loss of satellite signals caused by obstructions such as buildings, tunnels, and trees. To solve this problem, we introduce a GPS-/MSINS-/magnetometer-integrated urban navigation system based on context awareness. In this system, the data from the Micro Strapdown Inertial Navigation System (MSINS) are used to analyze and detect the context knowledge of vehicles, whose sensor errors can be compensated by the heuristic drift reduction algorithm for different motion situations. When GPS is available, the vehicle position can be estimated by unscented Kalman Filter, whereas in the case of GPS outages, the vehicle attitude is provided by an attitude and heading reference system and the motion constraints-aided algorithm is used to complete the positioning. In the experiment validation, the integrated navigation system is set up by low-cost inertial sensors. The result shows that the proposed system can achieve high accuracy when GPS is available. For most of the time without GPS, the system can guarantee the positioning precision of 10 m and compensate the errors of MSINS effectively, which fully satisfies positioning needs in complex urban environments.     

城市环境GPS/UWB组合系统定位精度研究

GPS可见卫星数量不足使得观测方程抗差性下降,在城市环境下一般难以精确定位。文章通过GPS/UWB组合定位抑制GPS观测粗差对定位精度的影响,提升组合系统的定位性能。实验证明,组合系统较GPS单系统在观测值数量、RDOP值、浮点解精度、双差模糊度浮点解精度和固定解精度方面均得到大幅改善。文章认为,借助UWB优秀的测距性能有效地提高了GPS的生存能力,特别是在城市峡谷等GPS信号遮挡严重的环境下应加设一定数量的UWB基准站,保证用户定位的连续性与准确性。     

Optimizing artificial neural network-based indoor positioning system using genetic algorithm

Abstract

The Global Positioning System (GPS) is expected to play an integral role in the development of digital earth; however, the GPS cannot provide positioning information in regions where a majority of the population spends their time, that is, in urban and indoor environments. Hence, alternate positioning systems that work in indoor and urban environments should be developed to achieve the vision of digital earth. Wi-Fi-based positioning systems (WPS) stand out because of the near-ubiquitous presence of the associated infrastructure and signals in indoor environments. The WPS-based fingerprinting is the most widely adopted technique for position determination, but its accuracy is lower than that of techniques such as time of arrival and angle of arrival. Improving the accuracy is still a challenging task because of the complex nature of the propagation of Wi-Fi signals. Here, a novel server-based, genetic-algorithm-optimized, cascading artificial neural network-based positioning model is presented. The model is tested in 2D and 3D indoor environments under varying conditions. The model is thoroughly investigated on a real Wi-Fi network, and its accuracy is found to be better than that of other well-known techniques. A mean accuracy of 1.9 m is achieved with 87% of the distance error within the range of 0–3 m.     

Enhanced MEMS-IMU/odometer/GPS integration using mixture particle filter

Dead reckoning techniques such as inertial navigation and odometry are integrated with GPS to avoid interruption of navigation solutions due to lack of visible satellites. A common method to achieve a low-cost navigation solution for land vehicles is to use a MEMS-based inertial measurement unit (IMU) for integration with GPS. This integration is traditionally accomplished by means of a Kalman filter (KF). Due to the significant inherent errors of MEMS inertial sensors and their time-varying changes, which are difficult to model, severe position error growth happens during GPS outages. The positional accuracy provided by the KF is limited by its linearized models. A Particle filter (PF), being a nonlinear technique, can accommodate for arbitrary inertial sensor characteristics and motion dynamics. An enhanced version of the PF, called Mixture PF, is employed in this paper. It samples from both the prior importance density and the observation likelihood, leading to an improved performance. Furthermore, in order to enhance the performance of MEMS-based IMU/GPS integration during GPS outages, the use of pitch and roll calculated from the longitudinal and transversal accelerometers together with the odometer data as a measurement update is proposed in this paper. These updates aid the IMU and limit the positional error growth caused by two horizontal gyroscopes, which are a major source of error during GPS outages. The performance of the proposed method is examined on road trajectories, and results are compared to the three different KF-based solutions. The proposed Mixture PF with velocity, pitch, and roll updates outperformed all the other solutions and exhibited an average improvement of approximately 64% over KF with the same updates, about 85% over KF with velocity updates only, and around 95% over KF without any updates during GPS outages.     

Deploying a Locata network to enable precise positioning in urban canyons

Locata is a new positioning technology developed by the Locata Corporation. At the beginning of 2007, the Institute of Engineering Surveying and Space Geodesy (IESSG) bought and received a network of Locata transceivers with two rovers. The purpose is to solve the challenges identified when surveying in dense multipath areas (i.e. urban canyons). In this paper, the technology is tested in an urban canyon scenario on the University park at the University of Nottingham. By comparing Locata position solutions with the true positions calculated with a total station and a carrier-phase GPS, the results show that centimetre-level accuracy is achievable in difficult environments in the presence of Wi-Fi signals. The rover’s estimated coordinates may diverge in some cases. Finally, a comparison study shows that Real Time Kinematic GPS and Locata technologies have similar accuracy when both are available.     

GPS/VRS 卫星定位服务网络建设与精度评定

虚拟参考站技术是近几年发展起来的,集Internet、无线通讯、计算机网络和GPS于一体的卫星定位技术。成都虚拟参考站卫星定位服务系统的建设,在设计上可满足全天候地向大成都地区用户提供厘米级实时动态定位服务。为了对该系统的实际定位精度进行客观的评价,从2 0 0 4年7月开展,历时两个月,全面完成了成都虚拟参考站卫星定位服务系统的精度评定工作,结果表明:在网内,水平方向上的精度可达2 .5cm ,垂直方向上的精度为4 . 5cm ,精度分布均匀;在网外,未模型化的距离相关误差的残余逐步增大,特别是距离网络中心大于1 2 0km以上时,定位精度开始衰减,为分米级。     

BeiDou、Galileo、GLONASS、GPS多系统融合精密单点

随着中国BeiDou系统与欧盟Galileo系统的出现以及俄罗斯GLONASS系统的恢复完善,过去单一的GPS导航卫星系统时代已经逐步过渡为多系统并存且相互兼容的全球性卫星导航系统(multi-constellation global navigation satellite systems,multi-GNSS)时代,多系统GNSS融合精密定位将成为未来GNSS精密定位技术的发展趋势。本文采用GPS、GLONASS、BeiDou、Galileo 4大卫星导航定位系统融合的精密单点定位(precise point positioning,PPP)实测数据,初步研究并分析了4系统融合PPP的定位性能。试验结果表明:在单系统观测几何构型不理想的区域,多系统融合能显著提高PPP的定位精度和收敛速度。4大系统融合的PPP收敛速度相对于单GNSS可提高30%~50%,定位精度可提高10%~30%,特别是对高程方向的贡献更为明显。此外,在卫星截止高度角大于30°的观测环境下,单系统由于可见卫星数不足导致无法连续定位,而多系统融合仍然可以获得PPP定位结果,尤其是水平方向具有较高的定位精度。这对于山区、城市以及遮挡严重的区域具有非常重要的应用价值。     

GPS/Pseudolite/INS integration: concept and first tests

This paper discusses the introduction of pseudolites (ground-based GPS-like signal transmitters) into existing integrated GPS/INS systems in order to provide higher availability, integrity, and accuracy in a local area. Even though integrated GPS/INS systems can overcome inherent drawbacks of each component system (line-of-sight requirement for GPS, and INS errors that grow with time), performance is nevertheless degraded under adverse operational circumstances. Some typical examples are when the duration of satellite signal blockage exceeds an INS bridging level, resulting in large accumulated INS errors that cannot be calibrated by GPS. Such a scenario, unfortunately, is a common occurrence for certain kinematic applications. To address such shortcomings, both pseudolite/INS and GPS/pseudolite/INS integration schemes are proposed here. Typically, the former is applicable for indoor positioning where the GPS signal is unavailable for use. The latter would be appropriate for system augmentation when the number and geometry of visible satellites is not sufficient for accurate positioning or attitude determination. In this paper, some technical issues concerned with implementing these two integration schemes are described, including the measurement model, and the appropriate integration filter for INS error estimation and correction through GPS and pseudolite (PL) carrier phase measurements. In addition, the results from the processing of simulated measurements, as well as field experiments, are presented in order to characterize the system performance. As a result, it has been established that the GPS/PL/INS and PL/INS integration schemes would make it possible to ensure centimeter-level positioning accuracy even if the number of GPS signals is insufficient, or completely unavailable. Electronic Publication     

GPS/BDS/GLONASS多系统组合定位分析

可见卫星数是评价导航系统定位性能的一个重要指标,也是系统可用性的基本要求。均方根差(亦称中误差)是观测精度的数据标准。本文通过实验分析了不同环境下的多系统组合的可见星数以及中误差,进而研究了多系统组合在不同环境中的可用性及定位精度。实验结果表明:在相同环境下,系统组合的可用性大幅提高,精度高于单GPS系统的精度,其中GPS/BDS/GLONASS三系统组合测量精度最高,GPS/BDS组合精度次之,GPS/GLONASS组合精度略低于GPS/BDS组合。     

RTK/INS紧组合算法在卫星数不足情况下的性能分析

设计了一套基于集中式卡尔曼滤波的实时动态定位（real-time kinematic,RTK）/惯性导航系统（inertial navigation system,INS）紧组合算法,通过实测车载数据对比分析了3颗可用卫星时的固定解和浮点解在位置漂移误差水平和模糊度恢复时间上的差异,验证了该算法在卫星较少情况下的良好性能。该算法在即使观测卫星不足4颗时使用固定解或浮点解进行滤波更新,提高了组合导航在复杂环境下的位置精度,并加快了模糊度恢复过程。实验结果表明,使用中等精度的惯导,在可见卫星数为3颗时,失锁30 s时的水平位置漂移误差为0.3 m;失锁60 s内,平均1~2 s就能可靠地恢复整周模糊度。在位置漂移误差与模糊度恢复方面,固定解和浮点解在GNSS信号短期部分失锁时的差异并不显著,但同时都明显优于信号完全失锁情形。     

BDS-3/GPS在遮挡环境下定位性能分析

针对在全球卫星导航系统(GNSS)信号易遮挡地区,单一系统可见卫星数较少,定位性能不理想甚至难以满足定位需求的问题,分析北斗三号(BDS-3)在不同区域遮挡环境下对定位性能的改善. 通过全球不同区域MGEX(Multi-GNSS Experiment)监测站的观测数据,采用GPS、BDS-3、BDS-3/GPS组合定位三种模式,在不同模拟遮挡环境下进行伪距单点定位,分析了各模式下可见卫星颗数、历元利用率、几何精度衰减因子(GDOP)值和定位精度. 结果表明:在北半球区域,相较于其他方向遮挡,GPS模式在低纬度地区南面遮挡的定位稳定性和精度最高,在中高纬度地区北面遮挡的定位稳定性和精度最高,BDS-3和BDS-3/GPS组合模式在低纬度地区各方向遮挡定位精度相当,在中纬度和中高纬度地区,北面遮挡的精度明显优于其他方向遮挡的定位精度. BDS-3/GPS组合定位模式,大大增加了可见卫星颗数,历元利用率提高,卫星空间几何结构改善,GDOP值降低,稳定性和定位精度明显优于单系统.      

融合地磁/WiFi/PDR的自适应粒子滤波室内定位

随着国民经济的快速发展,人们在室内活动的时间越来越长,室内空间环境也越来越复杂,对室内环境的位置与导航服务的需求也越来越高。由于地磁信号具有稳定性的特点,且WiFi技术已得到广泛部署,融合使用地磁和WiFi定位具有一定的优势。因此,本文基于Android系统智能手机作为接收设备,融合地磁、WiFi及行人航迹推算（PDR）技术,通过自适应粒子滤波模型和随机抽样一致性算法对采集的信号进行处理。试验证明,地磁、WiFi、PDR三者融合进行室内定位的方法与其他单类方法相比,实现了将室内定位精度的误差最小降低到1.02 m。     

多系统卫星融合定位数据的稳定性和精度比较分析

论述GNSS多系统融合定位的数学模型、分析各项误差处理策略以及参数估计方法,基于日本东京海洋大学RTKLIB软件进行GPS、GLONASS、Galileo、BDS多系统融合定位试验,并分析其动/静态定位稳定性和精度。试验结果表明:GNSS多系统融合收敛时间与GPS单系统相比缩短30%~50%,定位精度与GPS单系统相比可以提高20%~50%。此外,在卫星高度截止角大于40°和不利观测环境条件下,单系统可见卫星数不足,从而导致无法进行连续定位,但多系统融合可视卫星可获得比较好的定位精度,在建筑物密集区、山区和卫星遮挡较为严重的恶劣条件下具有实际应用价值。