摘要
针对利用惯导信息抑制末制导导引头量测随机误差的问题,提出了一种高精度惯导速度信息辅助的扩展卡尔曼滤波方法.利用高精度惯导速度信息描述导弹自身运动,采用一阶马尔科夫过程描述目标机动,构建基于弹目信息状态变量系统的弹目相对运动模型,通过扩展卡尔曼滤波方法实现对导引头测量随机误差的抑制.新方法实现了惯导信息、导引头量测信息的融合,克服了已有滤波方法运动模型建模时需考虑导弹制导控制因素的难点.仿真实验结果验证了该方法在导弹末制导过程中的有效性.
A novel extended Kalman filter(EKF) aided by precision inertial navigation system(PINS) velocity information is proposed for the application of terminal seeker random measurement error suppression.Missile motion was modeled by PINS velocity solution,while target maneuver by first-order Markov process.The dynamic model describing missile-to-target motion using the relative state vector was given,seeker random measurement error was then suppressed by using the novel EKF.The proposed filter could overcome the shortcoming of conventional filter in relative motion modeling,in which the factor of missile guidance and control might be involved.The validity of proposed filter in missile terminal guidance was then tested by simulation.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2010年第12期2850-2854,共5页
Acta Electronica Sinica
关键词
扩展卡尔曼滤波
弹目信息
高精度惯导系统
惯导速度信息
extended Kalman filters
missile-to-target information
precision inertial navigation system
speed information of inertial navigation system