Real-time accurate odometer velocity estimation aided by accelerometers

In strap-down gyro-compass in-motion alignment, the alignment accuracy depends not only on the quality of the gyroscopes and accelerometers, but also on the accuracy of the velocity provided by the aiding sensors such as odometers. To improve the accuracy of the in-motion alignment, real-time accurate odometer velocity estimation is required. In this paper, the effect of the noise of the odometer velocity on strap-down gyro-compass in-motion alignment accuracy is presented, based on the strap-down gyro-compass algorithm. A velocity tracking model is designed as the state model, to describe the relationship between and among the vehicle’s velocity, acceleration and jerk in the vehicle frame. Based on the velocity equation applied to strap-down navigation system mechanizations, the vehicle’s acceleration in the vehicle frame can be obtained from the specific forces measured by accelerometers. With the observations including the vehicle’s acceleration in the vehicle frame and the vehicle’s velocity in the vehicle frame obtained from the odometer using the first order difference algorithm, real-time velocity estimates are produced by a Kalman filter. The field test results show that the proposed method can successfully improve the accuracy of the odometer velocity. The comparison with the traditional method highlights the superior performance of the proposed method.     

基于WebGIS和GPRS的智能交通系统设计与实现

本文提出了一种基于WebGIS和GPRS的智能交通系统。该系统针对公交车辆将GIS、计算机技术、通信技术、数据采集与分析技术融合为一体,能实现对公交车辆的实时管理。通过管理调度中心的GIS可以对运行中的公交车辆进行监控和定位。目前本系统已经成功应用于公交部门。     

智能里程表检测仪硬件设计

现在市场上的里程表样式多种多样,但是很多里程表存在着汽车总里程数和车速不准确的问题,这就需要进行里程表的检测。该文提出了一种里程表检测仪的硬件设计,该设计采用ATmega16为核心的单片机系统,用变频器控制速度,实现了对不同调速比的里程表的检测。该里程表检测仪的系统电路简单可靠,用它来检测里程表方便且高效。     

前后向迭代滤波在SINS/OD组合导航中的应用

为了提高SINS/OD组合导航的精度,推导了载体坐标系下单位时间内位移增量之差的观测模型,利用残差X2检测对OD信号进行两层故障检测和隔离,使用前后向迭代滤波完成误差参数估计和校正.利用实车实验分别对Kalman滤波、1次迭代滤波、2次迭代滤波进行对比分析,结果表明2次迭代滤波精度最高,但相对于1次迭代滤波精度提高效果不够明显.从滤波精度和计算量上综合考虑,SINS/OD组合导航中1次迭代滤波效果最好.     

基于位置修正的井下车辆INS/Odometer 组合导航系统

车辆在井下的运动区域是在巷道内,根据此特点,在井下巷道设置已知点修正INS/Odometer组合导航过程的误差状态量,提高井下车辆导航精度。首先介绍了Odometer（里程计）位置和速度的计算方法,建立了INS/Odometer组合导航的系统模型和观测模型,在此基础上,构建井下巷道已知点位置修正的滤波方程,引入并行卡尔曼滤波器（Parallel-Kalman Filter）实现了组合导航的双重滤波,建立基于位置修正的井下车辆INS/Odometer组合导航系统。通过模拟数据和车载实验对比位置修正前后的INS/Odometer井下组合导航系统精度。实验证明,通过巷道已知点的位置修正,可以有效提高INS/Odometer井下组合导航效果,实时导航的平面精度从几十米提高到米级,能够满足井下车辆长时间的导航要求。     

GPS accuracy estimation using map matching techniques: Applied to vehicle positioning and odometer calibration

A test-bed application, called Map Matched GPS (MMGPS) processes raw GPS output data, from RINEX files, or GPS derived coordinates. This developed method uses absolute GPS positioning, map matched, to locate the vehicle on a road centre-line, when GPS is known to be sufficiently accurate. MMGPS software has now been adapted to incorporate positioning based on odometer derived distances (OMMGPS), when GPS positions are not available. Relative GPS positions are used to calibrate the odometer. If a GPS position is detected to be inaccurate, it is not used for positioning, or for calibrating the odometer correction factor. In OMMGPS, GPS pseudorange observations are combined with DTM height information and odometer positions to provide a vehicle position at ‘1 s’ epochs. The described experiment used GPS and odometer observations taken on a London bus on a predefined route in central of London. Therefore, map matching techniques are used to test GPS positioning accuracy, and to identify grossly inaccurate GPS positions. In total, over 15,000 vehicle positions were computed and tested using OMMGPS.In general, the position quality provided by GPS alone was extremely poor, due to multipath effects caused by the urban canyons of central London, so that odometer positioning was used much more often to position the vehicle than GPS. Typically, the ratio is 7:3 odometer positions to GPS positions. In the case of one particular trip, OMMGPS provides a mean error of position of 8.8 m compared with 53.7 m for raw GPS alone.     

Design and implementation of 30„ geometry PIG

This paper introduces the developed geometry PIG (Pipeline Inspection Gauge), one of several ILI (In-Line Inspection) tools, which provide a full picture of the pipeline from only single pass, and has compact size of the electronic device with not only low power consumption but also rapid response of sensors such as calipers, IMU and odometer. This tool is equipped with the several sensor systems. Caliper sensors measure the pipeline internal diameter, ovality and dent size and shape with high accuracy. The IMU (Inertial Measurement Unit) measures the precise trajectory of the PIG during its traverse of the pipeline. The IMU also provide three-dimensional coordination in space from measurement of inertial acceleration and angular rate. Three odometers mounted on the PIG body provide the distance moved along the line and instantaneous velocity during the PIG run. The datum measured by the sensor systems are stored in on-board solid state memory and magnetic tape devices. There is an electromagnetic transmitter at the back end of the tool, the transmitter enables the inspection operators to keep tracking the tool while it travels through the pipeline. An experiment was fulfilled in pull-rig facility and was adopted from Incheon LT (LNG Terminal) to Namdong GS (Governor Station) line, 13 km length.     

多种传动比里程表齿轮传动装置设计

里程表齿轮传动装置是工程车辆和汽车为速器的常用装置。选用的里程表不同，要求传动装置的传动比也不同。本文以一实际应用为例，阐述了在主动齿轮不变，壳体中心距不变的情况下，通过设置带有偏心距的输出齿轮安装座，并改变从动齿轮轴相对壳体的安装位置，来得到不同的中心距，通过齿轮变位，得出多种传动比的里程表齿轮传动装置的设计方法。     

行驶监视仪的静电放电抗扰度测试及其整改对策

本文对静电放电抗扰度试验标准和试验方法做了详细阐述.以行驶监视仪为例,介绍电子设备的静电放电抗扰度试验具体步骤及整改措施,并总结了提高静电放电抗扰度的方法.     

脉冲检测方法的霍尔传感器在里程表中的应用

里程表应用广泛,机械式里程表有其不足之处.设计智能自动化的里程表,利用霍尔效应原理,在电机中嵌入霍尔传感器,采用脉冲检测的方法实现测量行驶速度与里程,使用倍频电路提高系统的测量精度.设计了用户界面,可以实现超速报警及用户自设定初始上限速度,既可以实现测速也可以利用变频器来控制电机转速,实现了自动化和智能化.