摘要
为了处理机动目标跟踪过程中的非线性问题,提出了一种基于运动模型的扩展卡尔曼滤波(EKF)算法,该算法精度可以逼近最优估计,适用于任何可用状态空间模型表示的非线性系统。通过仿真表明利用运动模型的扩展卡尔曼滤波方法可以有效地抑制非视距误差(NLOS)对定位精度的影响,从而得到更高的定位跟踪效果。
In order to deal with mobile target tracking which contain non-linear, an EKF positioning and tracking algorithm based on kinematic model was proposed. This method can apply to any state-space model which is the nonlinear system, and the accuracy can approach to best of all. Simulation result shows that EKF can be used to effectively inhibit NLOS error and get higher precision.
出处
《重庆邮电大学学报(自然科学版)》
北大核心
2009年第1期50-52,60,共4页
Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition)
基金
教育部重点项目(207097)
关键词
扩展卡尔曼滤波
运动模型
定位跟踪
非视距误差
extended Kahnan filter (EKF)
kinematic model
positioning and tracking
NLOS