摘要
无迹卡尔曼滤波算法(UFK)以少量的采样点表示随机变量的分布,通过非线性系统传播,能以三阶精度获得非线性变换的均值和协方差的估计.文章将其应用于三维水下目标跟踪系统中.通过系统的MonteCarlo仿真,验证了该滤波算法比传统的扩展卡尔曼滤波具有更高的滤波精度.
This paper introduces the newly proposed unscented Kalman filter (UKF). In UKF, a minimal set of carefully chosen sample points is used to represent random variables distribution. And when propagated through the true nonlinear system, these sample pointes capture the mean and covariance accurately to the 3rd order for nonlinear transformation. In this paper, UKF is applied to a 3-D underwater target tracking system. The Monte Carlo simulation demonstrates that the UKF has higher filtering accuracy than conventional extended Kalman filter.
出处
《船舶工程》
CSCD
北大核心
2005年第3期24-28,共5页
Ship Engineering
关键词
工程测量技术
水下目标跟踪
无迹卡尔曼滤波
engineering measurement technique
underwater target tracking
unscented Kalman filter
