计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2010年
8期
214-216
,共3页
无迹卡尔曼滤波%扩展卡尔曼滤波%状态估计%雷达目标跟踪
無跡卡爾曼濾波%擴展卡爾曼濾波%狀態估計%雷達目標跟蹤
무적잡이만려파%확전잡이만려파%상태고계%뢰체목표근종
unscented Kalman filter%extended Kalman filter%state estimation%radar target tracking
提出一种基于加性无迹卡尔曼滤波的雷达目标跟踪方法.雷达跟踪系统为离散非线性系统,传统的解决方法是使用扩展卡尔曼滤波.无迹卡尔曼滤波用少量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方差的估计.用无迹卡尔曼滤波进行雷达目标跟踪.通过Monte Carlo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.
提齣一種基于加性無跡卡爾曼濾波的雷達目標跟蹤方法.雷達跟蹤繫統為離散非線性繫統,傳統的解決方法是使用擴展卡爾曼濾波.無跡卡爾曼濾波用少量採樣點錶示隨機變量的分佈,通過非線性繫統傳播,能以三階精度穫得非線性變換的均值和方差的估計.用無跡卡爾曼濾波進行雷達目標跟蹤.通過Monte Carlo倣真,驗證瞭該濾波算法比傳統的擴展卡爾曼濾波具有更高的濾波精度.
제출일충기우가성무적잡이만려파적뢰체목표근종방법.뢰체근종계통위리산비선성계통,전통적해결방법시사용확전잡이만려파.무적잡이만려파용소량채양점표시수궤변량적분포,통과비선성계통전파,능이삼계정도획득비선성변환적균치화방차적고계.용무적잡이만려파진행뢰체목표근종.통과Monte Carlo방진,험증료해려파산법비전통적확전잡이만려파구유경고적려파정도.
This paper introduces a method for radar target tracking based on Additive Unscented Kalman Filter(AUKF).In AUKF,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 points capture the mean and covariance accurately to the 3rd order for nonlinear transformation.AUKF is applied to a radar target tracking system.The Monte Carlo simulation demonstrates that the AUKF has higher filtering accuracy than conventional Extended Kalman Filter(EKF).
