摘要
为了获得移动机器人定位数据的真实性,减少各种随机误差对定位精度的影响,通过运动载体当前统计模型,取位置作为观测量建立移动机器人动态定位模型,同时针对传统卡尔曼滤波的不足进行了分析,提出自适应卡尔曼滤波算法,该算法始终保持噪声模型接近于真实模型,从而较好地解决了GPS动态定位中状态噪声与观测噪声建模不准确和时变问题,在此基础上,通过模拟噪声和轨迹曲线,进行了仿真,结果显示效果显著。
In order to obtain the real of positioning data of mobile robot and Io reduce the bad effect on position accuracy, Kalman filter is used to process raw data. By means of current static modal and choosing location as kinematic position. The deficiency of traditional and standard kalman filtering method used in dynamic filter is analyzed, an improved adaptive kalman filtering method is protposed. With this method, performance of GPS kinematic positioning filter is improved for moving robot. On the basis of theoretical analysis, the article obtains the result of computer simulation, and the precision of positioning is greatly increased.
出处
《舰船电子工程》
2005年第6期5-7,73,共4页
Ship Electronic Engineering
