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Unscented卡尔曼滤波对目标位置预测
引用本文:林瑞阳,杨东升,邱锋. Unscented卡尔曼滤波对目标位置预测[J]. 现代电子技术, 2014, 0(1): 34-37
作者姓名:林瑞阳  杨东升  邱锋
作者单位:[1]西北工业大学航天学院,陕西西安710072 [2]中国人民解放军96361部队,青海西宁810101
摘    要:采用一种针对目标位置预测只能测量角度信息的卡尔曼滤波算法,实现对目标的位置、速度和加速度的估计。由于是纯方位目标运动分析,所以一般的线性滤波方法不能使用,主要使用UKF滤波算法,并给出了具体步骤。通过仿真运算与以前的方法进行比较,发现该算法实现方便,并在滤波精度、稳定性和收敛时间等方面有了很大提高。

关 键 词:纯方位目标运动  非线性滤波  UKF  EKF

Target position prediction of Unscented Kalman filter
LIN Rui-yang,YANG Dong-sheng,QIU Feng. Target position prediction of Unscented Kalman filter[J]. Modern Electronic Technique, 2014, 0(1): 34-37
Authors:LIN Rui-yang  YANG Dong-sheng  QIU Feng
Affiliation:1. School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China; 2. Unit 96361 of PLA, Xi'ning 810101, China)
Abstract:A Kalman filter algorithms is provided to estimate the position, velocity and acceleration of the target, which could only measure the angle information of the target location prediction. Since it is the bearings-only target motion analysis, the general linear filtering methods can not apply. UKF filtering algorithm is mainly used in this paper, and the specific steps are given. Through the simulation calculation and comparison with the previous methods, it is found that this algorithm is easy to be implemented, and has great improvement in filtering accuracy, stability and convergence time.
Keywords:bearings-only target motion  nonlinear filtering  UKF  EKF
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