单输出系统最优自校正滤波新方法及其在跟踪系统中的应用
A NEW APPROACH OF OPTIMAL SELF-TUNING FILTERING FOR SINGLE OUTPUT SYSTEMS AND ITS APPLICATION TO TRACKING SYSTEMS
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摘要: 对于带未知噪声统计且含未知模型参数的单输出系统,本文用现代时间序列分析方法提出了一种新的自校正滤波方法,给出了具有渐近最优性的自校正滤波器,新方法的特点是基于ARMA新息模型通过计算自校正输出预报器和自校正观测噪声滤波器就可得到自校正状态滤波器,文中给出了在跟踪系统中的应用例子,仿真结果说明了新方法的有效性.Abstract: Using the modern time series analysis method, this paper presents a new self-tuning filtering approach for single output systems with unknown model parameters and unknown noise statistics. A self-tuning filter with asymptotically optimal behaviour is given by computing the self-tuning output predictors and observation noise filter based on ARMA innovation model. An application example to tracking system is given. Simulation results show usefulness of the new approach.