作　　者： ; ; ;

机构地区： 桂林电子科技大学信息与通信学院

出　　处： 《计算机工程》 2012年第22期244-247,250,共5页

摘　　要： 提出一种利用扩展卡尔曼滤波(EKF)算法实现移动台跟踪定位的改进算法。该算法在已获得移动台初始位置估计的基础上,利用EKF对移动台的运动轨迹进行多次估计,获取多条跟踪轨迹,剔除偏差较大的轨迹并进行加权平均的数据融合处理,获取一条较优轨迹。再结合距离门限值对较优轨迹的点迹进行匹配管理,实现对较优轨迹的平滑处理,获得最优跟踪轨迹。仿真结果表明,该算法计算复杂度低、鲁棒性强,定位精度明显高于传统EKF跟踪定位算法。 An improved tracking and localization algorithm for mobile stations based on Extended Kalman Filtering（EKF） is proposed. In this algorithm, EKF is used to obtain multiple tracking trajectories of a mobile station with its initial position estimation being obtained. Combining the technique of removing the trajectories with larger deviations and data fusion with weighted averaging, a better trajectory among the trajectories is found. Based on this, a distance threshold is coordinated with the matching management of the better trajectory＇s points for smoothing the better trajectory to obtain a best tracking trajectory. Simulation results show that the algorithm has low computational complexity, strong robustness as well as higher localization accuracy compared with traditional EKF tracking and localization algorithms.

关 键 词： 无线定位 移动台 轨迹跟踪 扩展卡尔曼滤波 数据融合 距离门限

领　　域： [自动化与计算机技术] [自动化与计算机技术]