基于Kalman滤波农用车辆导航定位方法  

Positions Research of Vehicle Navigation System Based on Kalman Filter

作　　者：籍颖[1,2] 刘兆祥[1] 刘刚[1] 张漫[1] 周建军[3] 

机构地区：[1]中国农业大学信息与电气工程学院,北京100083 [2]河北农业大学信息科学与技术学院,保定071001 [3]国家农业信息化工程技术研究中心,北京100097

出　　处：《农业机械学报》2009年第S1期13-17,共5页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家"863"高技术研究发展计划资助项目(2006AA10A304)

摘　　要：因RTD-GPS定位精度不能满足农田导航作业的需要,研究了一种提高农用车辆自动导航定位精度的方法。建立天线补偿模型,对GPS天线晃动引起的误差进行了补偿;建立基于Kalman滤波模型,融合多传感器信息;使用自主开发的基于VRS的GPS接收机,作为RTD-GPS。将RTD-GPS、电子罗盘以及速度传感器获得信息进行Kalman滤波,其结果和高精度GPS数据进行了比较。实验证明,直线跟踪中,平均偏差由1.6019 m减小到0.597 m;曲线跟踪中,平均偏差由1.2085 m减小到0.4861 m。ince the positioning accuracy of low accuracy GPS can not meet the requirements of agricultural production,a new navigation method is studied to improve the position accuracy.The compensate model is built to compensate for the libration caused by the antenna.A Kalman filter is developed,and a VRS-based receiver is used as the low accuracy GPS.The Kalman filter is applied to the data collected from the low accuracy GPS,compass and speed sensor.The data set collected from the RTK-GPS is used as a baseline to evaluate the performance of the filter.Experiment results indicated that the mean error was reduced from 1.601 9 m to 0.597 m straight line track,and from 1.208 5 m to 0.486 1 m in curve track.

关 键 词：车辆导航 定位 KALMAN滤波 信息融合 

分 类 号：S229.1[农业科学—农业机械化工程]