共查询到20条相似文献,搜索用时 93 毫秒
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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。 相似文献
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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。 相似文献
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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。 相似文献
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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。 相似文献
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A Particle Filtering Approach for Joint Detection/Estimation of Multipath Effects on GPS Measurements 总被引:2,自引:0,他引:2
Giremus A. Tourneret J.-Y. Calmettes V. 《Signal Processing, IEEE Transactions on》2007,55(4):1275-1285
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 相似文献
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《Journal of Location Based Services》2013,7(4):235-253
AbstractThe 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. 相似文献
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GPS GDOP classification via improved neural network trainings and principal component analysis 总被引:2,自引:0,他引:2
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. 相似文献
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Dragan Obradovic Henning Lenz Markus Schupfner 《The Journal of VLSI Signal Processing》2006,45(1-2):111-122
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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Axelrad P. Behre C.P. 《Proceedings of the IEEE. Institute of Electrical and Electronics Engineers》1999,87(1):133-144
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 相似文献
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Fusion of Sensor Data in Siemens Car Navigation System 总被引:1,自引:0,他引:1
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 相似文献