摘要
针对模型存在误差或状态突变下传递对准精度误差较大甚至发散等问题,提出了基于渐消记忆自适应卡尔曼滤波的传递对准方法,以设计的"速度+积分角速度"匹配模式为例进行仿真分析。仿真结果表明:基于渐消记忆自适应卡尔曼滤波的方法同经典卡尔曼滤波算法相比提高了传递对准的精度和收敛速度,是解决模型存在较大误差或状态突变下的传递对准问题的一种有效方法。
When conventional Kalman filter was applied to system model in transfer alignment,system state es-timation accuracy was not high even divergent when model error existed or status mutated.A fading memory a-daptive fliter algorithm was introduced in this paper.To ensure the accuracy of In-motion tansfer aligment in strapdown inertial system,a suboptimal filtering approach was constituted by introducing the fading memory factor in order to suppress the volatilization of system.And the "velocity and integral angular rate" matching mode which could restrain the effect of flexure deformation was designed.The simulation results showed that this method had better performance than conventional Kalman filter in the alignment accuracy and speed,it was a valid application method in transfer alignment.
出处
《探测与控制学报》
CSCD
北大核心
2014年第5期43-46,共4页
Journal of Detection & Control
基金
国家联合基金项目资助(U1330133)
关键词
捷联惯性导航系统
渐消记忆自适应滤波
卡尔曼滤波
传递对准
速度积分角速度
strapdown inertial navigation system
fading memory adaptive filter
Kalman filter
transfer align-ment
velocity and integral angular rate