摘要
我国自主研制的北斗卫星导航系统已开始应用于农业机械自动导航。针对广泛研究的无源北斗定位系统,由于定位接收机本身误差、环境噪声以及人为干扰等因素的影响,而导致相应的量测序列出现某些粗大的错误数据,使得导航定位不精确。用无迹卡尔曼滤波算法UKF(Unscented Kalman Filter)实现农业车载导航系统的非线性状态估计,避免了EKF方法的线性化近似过程及其引入的线性化截断误差,提高了算法的收敛速度和载体的定位精度。文中针对基于BD导航定位的喷雾机,对车载BD系统进行当前统计建模,用EKF和UKF方法分别进行了滤波仿真。仿真结果表明:在车载导航状态估计中,UKF滤波方法优于EKF滤波方法,定位精度可以达到1米左右。
The independent of BD satellite navigation system in our country has started to used in agricultural machinery automatic navigation. In view of the widespread study on passive BD positioning system,due to the inaccurate positioning receiver,environmental noise and the influence of factors such as human disturbance,and it causes the corresponding sequences to appear certain amount of gross error data,that there is no accurate navigation and positioning. UKF is used to implement agricultural vehicle navigation system of nonlinear state estimation,to avoid the EKF method of linearization approximation process and introduce the linearization of the truncation error. The algorithm's convergence speed and the load's positioning precision of UKF is far quicker than that of EKF. This paper based on the BD navigation and positioning of sprayer sets up the current statistical modeling for on-board BD system,using EKF and UKF method for filter simulation respectively. The simulation result shows that UKF is superior to EKF in nonlinear state estimation in the navigation state estimation,positioning accuracy can reach 3 meters.
出处
《信息技术》
2016年第10期76-80,共5页
Information Technology
基金
江苏省科技支撑项目(BE2014415)
江苏大学高级专业人才科研启动基金(11JDG123)
镇江市科技支撑项目(NY2014030)
关键词
北斗定位
卡尔曼滤波
定位精度
模型
BD navigation and positioning
Kalman lilter
positioning accuracy
model
