基于EKF的DR/激光测距组合导航算法研究  

Study on DR/Laser Rangefinder Integrated Navigation Algorithm Based on EKF

作　　者：曹学伟[1] 石杏喜[2] 左常清[3] 

机构地区：[1]山东科技大学测绘科学与工程学院,山东青岛266510 [2]南京理工大学理学院,江苏南京210094 [3]济宁矿业集团花园煤矿测绘科,山东济宁272200

出　　处：《山东科技大学学报（自然科学版）》2009年第2期84-87,共4页Journal of Shandong University of Science and Technology(Natural Science)

基　　金：中国博士后科学基金项目(2008440049)

摘　　要：航位推算(Dead Reckoning,DR)是一种常用的导航定位技术,其推算过程是一个累加过程,传感器的误差随时间的延长而积累,为此,将航位推算与激光测距组合起来用于智能车辆导航,确保系统在任何时候都能为运动智能车辆提供较为准确的导航信息。扩展卡尔曼滤波(Extended Kalman Filter,EKF)为一种非线性滤波器,是智能车辆组合导航系统中一种有效的数据融合方法。本文将EKF方法用于智能车辆组合导航的状态估计,仿真实验结果表明,EKF滤波能够有效地提高智能车辆的导航精度。The dead reckoning （DR） is a kind of navigation and positioning technology in common use. Since the course of dead reckoning is a cumulative course and the error of its sensor accumulates with the time. So, the dead reckoning can be integrated with the laser range finder for intelligence vehicles navigation to insure that the system can offer the exact navigation information for the moving intelligence vehicles at any time. Furthermore, as a kind of non-linear filter, the extended EKF is an effective data amalgamation method in the intelligence vehicles integrated navigation system. In the article, the EKF is used for estimating the state of intelligence vehicles integrated navigation. The result of the simulation experiment indicates that the EKF filter can improve the navigation precision of intelligence vehicles effectively.

关 键 词：扩展卡尔曼滤波 航位推算 激光测距仪 智能车辆 组合导航 

分 类 号：TP24[自动化与计算机技术—检测技术与自动化装置]