摘要
应用状态空间方法和现代时间序列分析方法［１］，基于白噪声估值器和输出预报器，提出了解决带输入的线性离散定常系统稳态最优和自校正Ｋａｌｍａｎ平滑新方法，并给出了在飞行器跟踪方面的应用，仿真结果说明了本文结果的实用性和有效性。
Using the state space method and the modern time series analysis method[1],based on white noise estimators and output predictors, this paper presents a new approach for solving the steady-state optimal self-tuning Kalman smoothing problem of linear discrete time-invariant systems with input and its application in flight vehicle tracking system.The simulation results show its applicability and its usefulness.
出处
《哈尔滨工业大学学报》
EI
CAS
CSCD
北大核心
1995年第5期17-22,共6页
Journal of Harbin Institute of Technology
关键词
自校正
卡尔曼平滑
飞行器
跟踪系统
Steady-state optimal Kalman smoothing
self-tuning Kalman smoothing
white noise estimators
flight vehicle tracking system
