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两传感器自校正信息融合Kalman滤波器
Two-sensor Self-tuning Information Fusion Kalman Filter
【摘要】 用现代时间序列分析方法,基于自回归滑动平均(ARMA)新息模型的在线辨识,对含有未知模型参数和噪声方差的两传感器线性离散随机系统,提出了自校正信息融合Kalman滤波器。它具有渐近最优性。一个仿真例子说明了其有效性。
【Abstract】 Using the modem time series analysis method, based on the on-line identification of the autoregressive movingaverage(ARMA)innovation model,a self-tuning information fusion Kalman filter is presented for two-sensor linear discretestochastic systems of containing the unknown model parameters and noise variances, which has asymptotic optimality. A simu-lation example shows its effectiveness.
【关键词】 信息融合;
辨识;
自校正Kalman滤波器;
两传感器;
【Key words】 information fusion; identification; self-tuning Kalman filter; two-sensor;
【Key words】 information fusion; identification; self-tuning Kalman filter; two-sensor;
【基金】 国家自然科学基金(69774019);黑龙江省自然科学基金(F01-15)
- 【文献出处】 科学技术与工程 ,Science Technology and Engineer , 编辑部邮箱 ,2003年04期
- 【分类号】TP212
- 【被引频次】26
- 【下载频次】218