...
首页> 外文期刊>Journal of Applied Research and Technology >Real time localization solution for land vehicle application using low-cost integrated sensors with GPS
【24h】

Real time localization solution for land vehicle application using low-cost integrated sensors with GPS

机译:使用低成本集成传感器使用GPS的实时定位解决方案

获取原文
           

摘要

The technique proposed in this research demonstrates a real time nonlinear data fusion solution based on extremely low-cost and grade inertial sensors for land vehicle navigation. Here, the utilized nonlinear multi-sensor data fusion (MSDF) is based on the combination between extremely low-cost micro electrical mechanical systems (MEMS) inertial, heading, pressure, and speed sensors in addition to satellite-based navigation system. The integrated navigation system fuses position and velocity states from the Global Positioning System (GPS), the velocity measurements from an odometer, heading angle observation from a magnetometer and navigation states from an inertial navigation system (INS). The implemented system performance is assessed through the post-processing of collected raw measurements and real time experimental work. The system that runs the real-time experiments is established on three connected platforms, two of them are based on a 32-bit ARMTM core and the third one is based 16-bit AVR ATMEL microcontroller. This microcontroller is connected to an on-board diagnostics (OBD) shield to collect the vehicle speed measurements. The raw data obtained from the integrated sensors is saved and post processed in MATLAB?. In normal conditions, the estimated position errors are reduced through the usage of INS/GPS integration with heading observation angle from a magnetometer. In GPS-denied environments, the integrated system uses the observations from INS, magnetometer in addition to the velocity from odometer to ensure a continuous and accurate navigation solution. A complementary filter (CF) is implemented to estimate and improve the pitch and roll angles calculations. In addition to that, an unscented Kalman filter (UKF) is used cascaded with the designed CF to complete the designed sensors fusion algorithm. Experimental results show that the designed MSDF can achieve a good level of accuracy and a continuous localization solution of a land vehicle in different GPS availability cases and can be implemented on the available in the market processors to be run in real time.
机译:本研究中提出的技术证明了一种基于极低成本和级别惯性传感器的实时非线性数据融合解决方案。这里,除了基于卫星的导航系统之外,利用的非线性多传感器数据融合(MSDF)基于极低成本微电路机械系统(MEMS)惯性,标题,压力和速度传感器之间的组合。集成导航系统熔断来自全球定位系统(GPS)的位置和速度状态,从里程表中的速度测量,从惯性导航系统(INS)从磁力计和导航状态的标题角度观察。通过收集的原始测量和实时实验工作的后处理来评估实施的系统性能。运行实时实验的系统在三个连接的平台上建立,其中两个基于32位ARMTM核心,第三个是基于16位AVR Atmel微控制器。该微控制器连接到板载诊断(OBD)屏蔽以收集车速测量。从集成传感器获得的原始数据被保存并在Matlab中处理后处理?在正常情况下,通过使用来自磁力计的标题观察角度的INS / GPS集成来减少估计的位置误差。在GPS拒绝环境中,除了从里程表的速度外,集成系统还使用来自INS,磁力计的观察,以确保连续和准确的导航解决方案。实施互补滤波器(CF)以估计和改善间距和辊角计算。除此之外,无需设计的Kalman滤波器(UKF)级联使用设计的CF级联,以完成设计的传感器融合算法。实验结果表明,设计的MSDF可以在不同GPS可用性情况下实现良好的准确性和陆地车辆的连续定位解决方案,并且可以在市场处理器中的可用中实现实时运行。

著录项

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号