FPGA与GPS—OEM板的串行通讯系统设计

以GARMIN公司的GPS-250EM板为例，介绍了GPS—OEM板的工作原理和通信协议，分析了NMEA-0183语句的数据格式及信息组成，研究了GPS—OEM板与FPGA的串行通讯方式，着重讨论了基于FPGA技术的GPS定位导航信息的读取问题，并给出了设计方案、相关软件流程和仿真结果。     

基于GPRS业务的GPS手持式信息传输系统

本文介绍了结合GPRS业务的GPS定位信息传输系统。主要介绍了基于iTrax02的GPS模块和基于CMS91的GPRS模块的硬件结构，相应的数据格式和开发方法。     

GPS时钟在广播电视系统中的应用

通过接收GPS卫星定位信号，获得高精度的时间信息输出，应用于广播电视系统中的时间授时，同步锁定，GPS时钟接收系统具有时间输出稳定，精度高，安全可靠等特点，本文将介绍LEITCH公司的GPS时钟接收系统及利用GPS接收板来获取GPS标准时间的方法。     

基于GPRS的GPS定位数据传输

利用GPRS网络，对GPS定位信息数据进行传输，以Intel的8031单片机为核心构架整个系统模块，给出整个系统的设计思想、硬件框图及系统的软件设计流程图并介绍了GPS信息数据格式，采用51汇编语言进行软件编程，通过单片机仿真实现了串行通信。     

基于C8051F040的简易GPS导航仪

随着科学技术的发展，GPS定位技术已经越来越走进普通人的生活，本文介绍了利用C8051F040单片机开发板、GPS接收机、液晶显示屏等实现的低成本、简单的局域GPS导航系统设计。系统通过串口实现和GPS接收机数据的通信，同时通过系统自制的基于矢量图形的数字地图，实现数字地图与导航信息的同步显示，并可以绘制载体的航迹。     

美国GPS应用服务技术文件简介

本文主要针对当前美国GPS提供的应用服务,介绍了其重要民用技术信息。这些技术信息包括GPS接口控制文件（ICD）、性能标准规范文件、美国联邦无线电导航计划及GPS＂无码/半无码＂用户保护声明。     

GPS/GPRS车辆监控系统中移动终端的开发

随着全球定位系统的发展，越来越多的民用车辆开始使用GPS定位技术实现定位、监控、导航等功能。介绍了一种GPS／GPRS车辆监控系统。提出在嵌入式平台上实现车载信息处理终端的开发方案，给出了车载信息处理终端的硬件和软件组成，详细介绍了各个硬件和软件模块的功能与实现方法。该方案充分发挥嵌入式平台的优点，实现了终端的高度集成，具有强大的信息处理能力。     

移动通信网中GPS定位信息传输

介绍了基于GSM和GPRS的GPS定位信息传输系统,通过各系统工作过程的研究对其性能进行了分析.展望了未来移动通信发展对GPS定位信息传输的深远影响.     

基于GPS和GIS技术的警车实时监测系统设计

介绍了基于地理信息系统（GIS）和全球定位系统（GPS）技术监测警车运行状况的一种设计方案。该方案在利用GPS系统获取的巡逻警车定位信息的基础上，结合GIS提供的强大的电子地图显示功能，不仅可以在电子地图上动态地显示警车的准确位置，而且能够迅速、准确地查询有关车辆信息，包括警车类型，警员装备等信息。实现了对警车的精确指挥调度、实时监控。保障了人民警察能够安全、迅速、准确地执行治安巡逻、治安防范的任务。     

GPS的数据资料接收装置与计算机间通信的研究

这篇文章对于GPS信息终端装置与计算机间通信进行处理的方法进行了解析,并且就这两种方法分别对于其通信协定进行了详尽的介绍,并在此基础之上以GARMIN系列的GPS信息终端装置作为例子,针对生产GPS信息终端装置的厂家合约进行了充分全面的解读,这一步骤可以帮助开发既能离线工作还能自动进行信息收集和处理工作的GPS内存数据模块,从而为人们实现技术集成手段提供一定程度的帮助。     

A Particle Filtering Approach for Joint Detection/Estimation of Multipath Effects on GPS Measurements

Multipath propagation causes major impairments to global positioning system (GPS) based navigation. Multipath results in biased GPS measurements, hence inaccurate position estimates. In this paper, multipath effects are considered as abrupt changes affecting the navigation system. A multiple model formulation is proposed whereby the changes are represented by a discrete valued process. The detection of the errors induced by multipath is handled by a Rao-Blackwellized particle filter (RBPF). The RBPF estimates the indicator process jointly with the navigation states and multipath biases. The interest of this approach is its ability to integrate a priori constraints about the propagation environment. The detection is improved by using information from near future GPS measurements at the particle filter (PF) sampling step. A computationally modest delayed sampling is developed, which is based on a minimal duration assumption for multipath effects. Finally, the standard PF resampling stage is modified to include an hypothesis test based decision step     

GPS接收机抗干扰性能仿真研究

从压制式干扰对GPS信号捕获的影响和对GPS信号跟踪的影响2个方面分析了对GPS接收机实施干扰的可行性;进行了GPS干扰性能仿真,建立了P码GPS接收机、P码GPS信号和GPS下行信道的数学模型和仿真模型;对单载波干扰信号、阶梯波扫频干扰信号和噪声调频干扰信号下P码GPS接收机的抗干扰容限进行了仿真实验,并给出了实验结果,最后对抗干扰容限仿真实验结果进行了分析。     

On processing GPS tracking data of spatio-temporal car movements: a case study

Abstract

The advancement of GPS technology has made it possible to use GPS devices as orientation and navigation tools, but also as tools to track spatio-temporal information. GPS tracking data can be broadly applied in location-based services, such as spatial distribution of the economy, transportation routing and planning, traffic management and environmental control. Therefore, knowledge of how to process the data from a standard GPS device is crucial for further use. Previous studies have considered various issues of the data processing at the time. This paper, however, aims to outline a general procedure for processing GPS tracking data. The procedure is illustrated step by step by the processing of real-world GPS data of car movements in Borlänge in the centre of Sweden.     

GPS GDOP classification via improved neural network trainings and principal component analysis

Geometric dilution of precision (GDOP) is an engineering expression that denotes how well the constellation of global positioning system (GPS) satellites is organised geometrically. In the analysis of received signals, it is often essential to invert and transform the data matrices. This requires tremendous computational burden on the navigator’s processor. Since classification of GPS GDOP is a non-linear problem, neural networks (NNs) can be used as an acceptable solution. Since the back propagation (BP) does not have sufficient speed to train a feed-forward NN, in this paper several improved NN trainings, including Levenberg–Marquardt (LM), modified LM, and resilient BP (RBP), scaled conjugate gradient, one-step secant (OSS) and quasi-Newton methods are proposed to classify the GPS GDOP. In this study, in order to have uncorrelated and informative features of the GPS GDOP, principal component analysis (PCA) is used as a pre-processing step. The simulation results show that using the RBP and PCA leads to greater accuracy and lower calculation time comparing with other existing and proposed methods and it can improve the classification accuracy of GPS satellites to about 99.65%. Moreover, the modified LM is the fastest algorithm that requires only 10 iterations for training the NN and it can be used in online applications.     

Fusion of Map and Sensor Data in a Modern Car Navigation System

The main tasks of car navigation systems are positioning, routing, and guidance. This paper describes a novel, two-step approach to vehicle positioning founded on the appropriate combination of the in-car sensors, GPS signals, and a digital map. The first step is based on the application of a Kalman filter, which optimally updates the model of car movement based on the in-car odometer and gyroscope measurements, and the GPS signal. The second step further improves the position estimate by dynamically comparing the continuous vehicle trajectory obtained in the first step with the candidate trajectories on a digital map. This is in contrast with standard applications of the digital map where the current position estimate is simply projected on the digital map at every sampling instant.

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Satellite attitude determination based on GPS signal-to-noise ratio

A method is presented for coarse attitude determination using the Global Positioning System (GPS) signal-to-noise ratio (SNR) from a single antenna mounted on a near-Earth satellite. It comprises a calibration procedure and a single-point optimal solution for the orientation of the antenna boresight vector. The calibration step creates an empirical mapping of the SNR to the angle between the antenna boresight and the GPS line-of-sight vector, based upon a ground or flight data set. The rms attitude accuracy at the level of 3°-10° is demonstrated with actual flight data from several spacecraft. Performance is shown to depend strongly on the number of GPS signals available and the quality of the calibration mapping function. The method is suitable as a backup attitude sensor for low-cost satellite and terrestrial applications, and as a coarse reference for ambiguity resolution and integrity verification of phase-based GPS attitude-determination algorithms     

高轨GPS信号可用性分析

针对目前国内关于高轨GPS信号可见性研究大多以几何分析为主,工程实现指导性不强的缺点,文章以GPS接收机系统指标设计为目标,引入接收机等价增益概念,结合空间几何模型与信号链路传播特点,考虑GPS发射天线增益、接收机信号处理时间、GPS星座状况、接收天线增益等实际因素,对适用于高轨GPS信号可用性进行分析。仿真表明-180 dBW接收功率下,通过接收更多GPS旁瓣信号,GPS接收机能有效应用于高轨航天器导航。     

LAMBDA算法在卫星导航定位中的应用研究

卫星导航定位中,基于载波相位观测值的RTK定位技术能够在达到厘米级的定位精度,其核心技术是整周模糊度的快速解算。采用LAMBDA方法能快速解算整周模糊度完成初始化,实时周跳检测,搜索并固定新的模糊度。利用2个NovAtel接收机采集数据,对采集到的数据进行仿真验证。仿真结果显示,该方法缩短了搜索的时间,定位结果达到了精度要求。     

浅析GPS干扰技术

介绍了导航战中的GPS干扰技术,针对GPS干扰技术的特点,阐述了GPS信号的侦测,GPS干扰技术体制,建立GPS分布式、立体干扰系统。     

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