摘要
本文用现代时间序列分析方法对雷达跟踪系统提出了一种新的自校正α-β跟踪滤波器,它有如下优点:1) 可处理带未知噪声统计和含未知模型参数的跟踪系统;2) 基于ARMA新息模型的在线辨识,可简单地计算α-β滤波器的参数;3) 避免解稳态Riccati方程;4) 具有渐近最优(自校正)性。仿真例子说明了其有效性。
For the radar tracking systems, this paper presents a new self-tuning α-β tracking filter, which has the following advantages: 1) The tracking systems with unknown noise statistics and model parameters can be handled; 2) Ba ed on the on-line identification of ARMA innovation model, the parameters of the α-β filter can simply be calculated; 3) To avoid solving the steady-state Riccati equation, and 4) It has the assymptotically optimal (self-tuning) behaviour. A simulation example shows the usefulness of the proposed results.
出处
《自动化学报》
EI
CSCD
北大核心
1992年第6期720-723,共4页
Acta Automatica Sinica
基金
黑龙江省自然科学基金
关键词
α-β
跟踪滤波器
自校正
滤波器
Radar tracking systems
α β tracking filter
self-tuning Kalman filter.