卡尔曼滤波器在弹道重构中的应用与仿真  

Simulation and Application of Kalman Filter in Trajectory Reconstruction

作　　者：杨荣军[1] 王良明[1] 修观[1] 

机构地区：[1]南京理工大学动力工程学院,南京210094

出　　处：《火力与指挥控制》2011年第11期156-158,共3页Fire Control & Command Control

基　　金：南京理工大学科研发展基金资助项目(XKF05031)

摘　　要：弹道重构是评价弹道精度、有效实施弹道控制技术的关键。为了有效地利用卡尔曼滤波器实施弹道重构技术,建立了适用于在线弹道重构的非线性弹道模型,引入了积分预测算法,能减少离散卡尔曼滤波器一步预测的误差。给出并分析了适用于弹道重构的EKF和UKF算法,UKF避免了处理非线性系统时的线性化问题。仿真试验对比了两种方法的重构精度,结果表明基于UKF弹道重构精度高、收敛快,并且更稳健。The trajectory reconstruction is the crux to evaluate the ballistic accuracy and to carry out the control technique of trajectory effectively.Aming at applying Kalman filter to trajectory reconstruction,the nonlinear model of the ballistic is established,which is suitable for on-line trajectory reconstruction.The integral forecasting algorithm can reduce forecasting error of the discrete Kalman filter,which is inducted in this paper.This paper discusses the formulation of two trajectory reconstruction tools for projectiles,and their implementation for the reconstruction with the measurement data.UKF avoids the linearization of the nonlinear systems.Both Extended Kalman Filter and Unscented Kalman Filter techniques are employed to reconstruct the trajectory of the projectiles in the simulation. The results show that UKF has the better performance and applicability in the trajectory reconstruction.

关 键 词：弹道学 弹道重构 卡尔曼滤波器 UT变换 仿真 

分 类 号：TJ012.3[兵器科学与技术—兵器发射理论与技术]