摘要
为了克服"当前"统计模型下的卡尔曼滤波算法在跟踪匀速目标时误差较大的缺陷,文章分析了造成此缺陷的原因,通过改进基于截断正态分布下的加速度方差模型,提高了对非机动目标的跟踪精度,仿真结果表明,该算法能够准确描述各种机动情况。
In order to overcome the bigger error defect of Kalman filtering algorithm in tracking the moving target at uniform velocity in ＂Current＂ statistical model,the reason why this defect occurred is analyzed.By improving the acceleration variance model based on truncation normal Distribution,the tracking accuracy for non-maneuvering target can be improved.The simulation results show that this algorithm can describe various maneuvering situation accurately.
出处
《火控雷达技术》
2009年第4期88-90,94,共4页
Fire Control Radar Technology
关键词
机动目标跟踪
卡尔曼滤波
加速度模型
仿真
tracking maneuvering target
kalman filter
acceleration model
simulation
