自适应Kalman滤波器及其应用
An Adaptive Kalman Filter and ist Application
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摘要: 对于带未知噪声统计的单输出系统,本文提出了一种新的自适应Kalman滤波器.应用 现代时间序列分析方法,基于ARMA新息模型的滑动平均(MA)参数的在线辨识,提出了 稳态最优Kalman滤波器增益估计的一种新算法,比Mehra的算法简单.同时还提出了辨 识滑动平均(MA)模型参数的一种新的自适应Kalman滤波算法.此外,给出了在雷达跟 踪系统中的应用,且仿真结果说明了本文算法的有效性.
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关键词:
- 自适应Kalman滤波 /
- 稳态滤波增益估计 /
- ARMA新息模型 /
- 辨识 /
- 雷达跟踪系统
Abstract: A new adaptive Kalman filter is presented for the single output system with unknown noise statistics. By a time series analysis, a new and simpler estimation algorithm for the gain of the steady-state optimal Kahnan filter is given. A new adaptive Kalman filtering algorithm is also given for identifying the parameters of moving average (MA) model. An application to a radar tracking system is given to show the usefulness of the proposed new algorithms.
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