Fusion of Sensor Data in Siemens Car Navigation System

Car navigation systems have three main tasks, namely 1) positioning; 2) routing; and 3) navigation (guidance). Positioning of the car is carried out by appropriately combining information from several sensors and information sources, including odometers, gyroscopes, Global Positioning System (GPS) information, and digital maps. This paper describes two sensor-fusion steps implemented in commercial Siemens car navigation systems. The first step is the fusion of the odometer, gyroscope, and GPS sensory information. The dynamic model of the car movement is implemented in a Kalman filter, which relays the GPS signal as a teacher. In the second step, the available digital map is used to find the most likely position on the roads. Contrary to the standard application of the digital map, where the current estimated car position is just projected on the road map, the approach presented here compares the features of the integrated vehicle path with the features of the candidate roads from the digital map. In addition, this paper presents the results of the experimental drives. The developed car navigation system was awarded the best car navigation system among ten competing systems in 2002 by the Auto Build magazine     

Adaptive fuzzy-network-based C-measure map-matching algorithm forcar navigation system

Most car navigation systems estimate the car position from dead reckoning and the Global Positioning System (GPS). However, because of the unknown GPS noise, the estimated position has an undesirable error. To solve this problem, a map-matching method is introduced, which uses a digital road map to correct the position error. In this paper, a novel adaptive-fuzzy-network-based C-measure algorithm is proposed, which can find the exact road on which a car moves. The C-measure algorithm is easy to calculate, and calculation time does not increase exponentially with the increase of junctions. For the experiments, a car navigation system is implemented with a small number of sensors. The real road experiments demonstrate the effectiveness and applicability of the proposed algorithm and the developed car navigation system     

基于ID卡定位的智能汽车自主导航系统设计

基于智能汽车的发展,本文设计了一种智能车的自主导航系统.该系统以ID卡定位为主导,模拟GPS系统来实现自主导航功能,以达到小车寻迹到达指定位置的目的.通过调试,小车可根据路面情况进行寻迹避障和定位,导航精度在3厘米之内.     

New Map‐Matching Algorithm Using Virtual Track for Pedestrian Dead Reckoning

In this paper, a map‐matching (MM) algorithm which combines an estimated position with digital road data is proposed. The presented algorithm using a virtual track is appropriate for a MEMS‐based pedestrian dead reckoning (PDR) system, which can be used in mobile devices. Most of the previous MM algorithms are for car navigation systems and GPS‐based navigation system, so existing MM algorithms are not appropriate for the pure DR‐based pedestrian navigation system. The biggest problem of previous MM algorithms is that they cannot determine the correct road segment (link) due to the DR characteristics. In DR‐based navigation system, the current position is propagated from the previous estimated position. This means that the MM result can be placed on a wrong link when MM algorithm fails to decide the correct link at once. It is a critical problem. Previous algorithms never overcome this problem because they did not consider pure DR characteristics. The MM algorithm using the virtual track is proposed to overcome this problem with improved accuracy. Performance of the proposed MM algorithm was verified by experiments.     

一种基于RFID原理的交通信息获取系统与车辆定位方法

 车辆的无线定位技术已成为近年来的一个研究热点。该文首先提出了一种基于RFID(射频识别)技术的交通信息获取系统,并在此基础上,提出了一种新的多基站TDOA(到达时间差)车辆定位方法。该方法是一种基于鲁棒性估计的两步定位方法。第1步利用多个基站的TDOA信息通过鲁棒性估计找到车辆的大致位置,然后进一步采用与车辆距离最近的3个基站的TDOA信息对车辆进行精确定位。该方法可有效地克服传统Chan算法当信号衰减引起TDOA估计误差较大时性能迅速恶化的问题。仿真实验结果表明该方法的定位精度优于传统的Chan算法和基于直接平均的2次定位法,可满足交通信息获取系统中对机动车辆定位的要求。     

头盔式GPS导航系统导航软件的设计

介绍在头盔式GPS导航系统的硬件平台上开发的导航软件NaviBoot,用于实现实时图上导航,具备以下功能：从GPS接收模块获得导航数据流;解析数据,计算出经纬度,海拔高度,速度,方位角,时间等信息;导入导航地图,将位置坐标显示在导航图上;同时还具有记录历史路径,查看地图信息等功能。     

一种基于电子地图的GPS定位技术

主要阐述在Windows操作系统下结合GPS技术和电子地图技术，将用户当前的地理位置在电子地图上准确地表示出来的一种实时GPS定位技术。从开发一个小型GPS／GIS系统所必须涉及到的几个方面入手，遵循从GPS信号的接收、处理开始，到电子地图的开发制作，最后到GPS定位功能的实现的步骤，其思路清晰、浅显易懂，对于初学者和开发复杂的GPS／GIS系统有很好的参考价值。实验表明，以此种方法设计的小型GPS定位系统，精度较高，可以满足一般的民用定位要求。     

Particle filters for positioning, navigation, and tracking

A framework for positioning, navigation, and tracking problems using particle filters (sequential Monte Carlo methods) is developed. It consists of a class of motion models and a general nonlinear measurement equation in position. A general algorithm is presented, which is parsimonious with the particle dimension. It is based on marginalization, enabling a Kalman filter to estimate all position derivatives, and the particle filter becomes low dimensional. This is of utmost importance for high-performance real-time applications. Automotive and airborne applications illustrate numerically the advantage over classical Kalman filter-based algorithms. Here, the use of nonlinear models and non-Gaussian noise is the main explanation for the improvement in accuracy. More specifically, we describe how the technique of map matching is used to match an aircraft's elevation profile to a digital elevation map and a car's horizontal driven path to a street map. In both cases, real-time implementations are available, and tests have shown that the accuracy in both cases is comparable with satellite navigation (as GPS) but with higher integrity. Based on simulations, we also argue how the particle filter can be used for positioning based on cellular phone measurements, for integrated navigation in aircraft, and for target tracking in aircraft and cars. Finally, the particle filter enables a promising solution to the combined task of navigation and tracking, with possible application to airborne hunting and collision avoidance systems in cars     

基于GNSS_CN高速公路自动收费系统的研究与设计

本文独创性的提出将多卫星定位系统融合来提高定位精度,并采用高可靠、高精度的定位应用于高速公路等收费系统中,实现了基于GNSS/CN高速公路收费车载单元的研究与设计.介绍了车载单元工作原理,以及硬件和软件系统的设计方案,通过硬件和软件设计与调试,相比原有单一卫星定位系统,在多卫星定位系统融合的基础上,实现了更高精度的定位.车载单元利用GPS或/和BD等系统获取车辆的位置、速度等信息,通过蜂窝网络和控制中心进行通信,将位置、速度等信息发送到控制收费中心,可在控制收费中心和车载单元上进行地图匹配,动态显示车辆位置、速度以及收费等信息.该成果已成功试运行.     

车载定位系统中综合地图匹配算法研究

基于加拿大亚伯达省政府远程运输RTS系统开发,在分析影响地图匹配性能因素的基础上,提出了一种基于高精密数字地图的综合地图匹配算法,融合了几何匹配算法和路网拓扑结构,充分利用车辆行驶的连续性,结合历史行驶数据选取投影道路,实现准确定位,且算法计算量小,可用于嵌入式实时系统.通过实际跑车试验证明该匹配算法精度高、效率好,具有较好的实用价值.     

Multimedia Corpus of In-Car Speech Communication

An ongoing project for constructing a multimedia corpus of dialogues under the driving condition is reported. More than 500 subjects have been enrolled in this corpus development and more than 2 gigabytes of signals have been collected during approximately 60 minutes of driving per subject. Twelve microphones and three video cameras are installed in a car to obtain audio and video data. In addition, five signals regarding car control and the location of the car provided by the Global Positioning System (GPS) are recorded. All signals are simultaneously recorded directly onto the hard disk of the PCs onboard the specially designed data collection vehicle (DCV). The in-car dialogues are initiated by a human operator, an automatic speech recognition (ASR) system and a wizard of OZ (WOZ) system so as to collect as many speech disfluencies as possible. In addition to the details of data collection, in this paper, preliminary results on intermedia signal conversion are described as an example of the corpus-based in-car speech signal processing research.     

Less is more [intelligent speed adaptation for road vehicles]

The use of sophisticated in-car technology to enforce urban speed limits and improve road safety is an idea whose time could well have come. To the great majority of motorists, speed bumps are, at best, a 'necessary evil'. However, if the results of recent trials in Sweden involving intelligent speed adaptation (ISA) technology are anything to go by then the days of this contentious feature of our urban roads could well be numbered. Between 1999 and 2002 government funding of SEK75m (#5.64m) was provided to install ISA systems in 5000 test vehicles distributed amongst four Swedish municipalities (Borlange, Lidkoping, Lund and Umea), and the results of these trials have apparently greatly exceeded the expectations of even ISA technology's keenest proponents within the Swedish National Road Administration (SNRA). ISA systems are, a combination of several existing technologies being put together in a new way. Many cars at the expensive end of the market are now being provided with satellite navigation systems as standard, where each vehicle is fitted with a Global Positioning System (GPS) transmitter/receiver, so that the precise position of the vehicle can be determined, and a GSM mobile phone link, so that this position can be integrated with a detailed and accurate digital roadmap maintained by the satellite navigation service provider. ISA technology, simply put, merely adds data on speed limits to the digital road map, so that each vehicle 'knows' what the maximum legal speed is on any road that it happens to be travelling along.     

Tunnel lane‐positioning system for autonomous driving cars using LED chromaticity and fuzzy logic system

Currently, studies on autonomous driving are being actively conducted. Vehicle positioning techniques are very important in the autonomous driving area. Currently, the global positioning system (GPS) is the most widely used technology for vehicle positioning. Although technologies such as the inertial navigation system and vision are used in combination with GPS to enhance precision, there is a limitation in measuring the lane and position in shaded areas of GPS, like tunnels. To solve such problems, this paper presents the use of LED lighting for position estimation in GPS shadow areas. This paper presents simulations in the environment of three‐lane tunnels with LEDs of different color temperatures, and the results show that position estimation is possible by the analyzing chromaticity of LED lights. To improve the precision of positioning, a fuzzy logic system is added to the location function in the literature [1]. The experimental results showed that the average error was 0.0619 cm, and verify that the performance of developed position estimation system is viable compared with previous works.     

GPS导航系统中电子地图处理及匹配算法研究

针对传统的车载导航系统对于车辆位置的获取能力存在速度慢、精度低等诸多问题,从匹配算法和电子地图处理两个方面入手给出了相应的解决办法。结果表明,预处理后的电子地图结合我们提出的匹配算法能够极大改善匹配结果的实时性和准确性。     

GPS/DR组合导航性能增强技术

为了提高全球定位系统(GPS)信号短时中断时地面车辆自主导航精确度,提出了GPS信号中断时采用车辆不完全约束条件和里程仪速度信息作为量测,辅助惯性导航系统实现车辆航位推算(DR)自主导航的方案;推导了该方案的GPS/DR组合导航的卡尔曼滤波方程;并进行了计算机仿真研究和地面车载试验,结果显示GPS信号中断90 s,DR自主导航误差为20 m,能够满足部分地面车辆短时高精确度自主定位要求。     

基于GPS及LBS的移动终端定位研究

本文主要介绍了一种可移动终端的定位方案,如航行的船只,移动的车辆.方案主要基于GPS和LBS理论,并以硬件终端为载体,android系统为平台.分析了两种定位方法的原理及定位方案的设计流程.最终实现对可移动终端的定位和监控.     

基于Wi-Fi即时定位与映射像素模板匹配的室内运动地图构建与定位

传统指纹定位方法由于建库人力时间开销大、系统通用性不强约束着指纹定位系统的推广,为了解决该问题同时结合即时定位与映射(SLAM)技术的优势,该文提出一种新的Wi-Fi/微机电系统(MEMS)融合室内运动地图构建与定位方法。首先利用行人航迹推算(PDR)、最小描述长度(MDL)原则和基于密度的空间聚类算法(DBSCAN)对众包运动轨迹进行预处理,提出基于轨迹主路径的运动地图构建方法。之后提出基于像素模板的地图匹配方法获取地图的绝对位置,并采用抗差扩展卡尔曼滤波(EKF)对目标位置进行最优估计。实验结果表明,所提聚类方法可以准确构建各区域运动地图,在少量的人力时间开销下实现较高的定位精度。     

Smart framework for GNSS‐based navigation in urban environments

Intelligent Transport System applications require accurate and reliable positioning. When stand‐alone global positioning system (GPS) is used in urban areas, the results dramatically degrade, because of signal outages and multipath. This paper unveils new signal processing techniques for carrier phase‐based navigation in urban environments. The techniques identify multipath or weak signals using carrier phase based receiver autonomous integrity monitoring, and abnormal signals and situational measurements are eliminated or estimated. To estimate the carrier phase during a short time period when GPS signals is blocked, this paper uses carrier phase statistics. The performance of the proposed method is verified, through a car test. The test environment has many signal outages and multipath because of high buildings. Many abnormal signal conditions occurred during the test, and the results confirmed that the proposed method performed better than the basic stand‐alone GPS approach when compared with GPS/inertial navigation system (INS) integrated navigation results. Copyright © 2015 John Wiley & Sons, Ltd.     

基于GPS_GPRS车辆监控终端设计与实现

车辆定位监控系统作为高新技术中智能交通系统的一个重要分支,90年代以后得到了很大的发展。定位监控系统的发展主要受到通信网络和地理信息系统发展情况的制约。文中介绍了一种基于GPS（全球定位系统）和GPRS（通用分组无线业务）的车辆定位监控系统,给出了车载终端部分的硬件、软件的设计以及实际测试结果分析。由于采用GPRS网络进行数据传榆,使得此车辆监控系统具有实时性好、实用性好和扩展性好等优点。     

一种HSGPS接收机的设计与验证

分析了GPS弱信号的特点,探讨了只存在NLOS型信号时影响GPS定位的主要技术因素。以u-blox公司的LEA-5S为基础,设计和验证了针对弱信号环境下车辆定位的HSGPS接收机。最后,通过测试其启动的TTFF和定位准确度,论证了HSGPS接收机设计及弱信号环境下定位车辆应用的可行性。