摘要
为保证获得数据的实时性以及滤除数据在获取过程中存在的一系列野值干扰,利用鲁棒滤波理论对最速跟踪微分器的跟踪和抗野值功能进行了改进,利用误差反馈的思想,对最速跟踪微分器进行实时在线的补偿修正,并将改进型跟踪微分器与标准最速跟踪微分器和鲁棒Kalman滤波器仿真结果进行了比较,表明经改进的最速跟踪微分器有更好的跟踪、滤波以及抗野值效果。
To obtain the real-time survey data and eliminate the unfavorable influence of outliers on the filter,the functions of steepest tracking-differentiator on tracking and outliers rejection are improved through Robust Filtering Method,through the error feed back,give the modification and compensation to steepest tracking-differentiator.Compare the filting effect simulation of the improved steepest tracking-differentiator to steepest tracking-differentiator and robust Kalman filter.After amelioration,the improved steepest Tracking-differentiator has the better performance on tracking and outliers rejection than steepest Tracking-differentiator and robust Kalman filter.
出处
《火力与指挥控制》
CSCD
北大核心
2010年第12期138-140,共3页
Fire Control & Command Control
基金
海装重点基金资助项目
关键词
最速跟踪微分器
鲁棒Kalman滤波
跟踪
抗野值
steepest tracking-differentiator
robust kalman filtering
tracking
outliers rejection
