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含未知参数的自校正融合Kalman滤波器及其收敛性 预览 被引量:8

Self-tuning Fusion Kalman Filter with Unknown Parameters and Its Convergence
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摘要 对于带未知模型参数和噪声方差的多传感器系统,基于分量按标量加权最优融合准则,提出了自校正解耦融合Kalman滤波器,并应用动态误差系统分析(Dynamic error system analysis,DESA)方法证明了它的收敛性.作为在信号处理中的应用,对带有色和白色观测噪声的多传感器多维自回归(Autoregressive,AR)信号,分别提出了AR信号模型参数估计的多维和多重偏差补偿递推最小二乘(Bias compensated recursive least—squares,BCRLS)算法,证明了两种算法的等价性,并且用DESA方法证明了它们的收敛性.在此基础上提出了AR信号的自校正融合Kalman滤波器,它具有渐近最优性.仿真例子说明了其有效性. For the multisensor systems with unknown model parameters and noise variances, a self-tuning decoupled fused Kalman filter is presented based on the optimal fusion rule weighted by scalars for components. Its convergence is proved by using the dynamic error system analysis (DESA) method. As an application to signal processing, the multidimensional and multiple bias compensated recursive least-squares (BCRLS) algorithms for estimating the AR parameters are presented for the multisensor multidimensional autoregressive (AR) signal with white and colored measurement noises. The equivalence between the two BCRLS algorithms is proved. The convergence of the two BCRLS algorithms is proved by DESA method. Further more, a self-tuning fused Kalman filter for the AR signal is presented, which has asymptotic optimality. A simulation example shows the effectiveness.
作者 陶贵丽 邓自立 TAO Gui-Li1, 2 DENG Zi-Li ( 1. Department of Automation, Heilongjiang University, Harbin 150080 2. Computer and Information Engineering College, Heilongjiang Institute of Science and Technology, Harbin 150027)
出处 《自动化学报》 EI CSCD 北大核心 2012年第1期 109-119,共11页 Acta Automatica Sinica
基金 国家自然科学基金(60874063),黑龙江省教育厅科学技术研究项目(11553101),黑龙江大学自动控制重点实验室项目资助
关键词 多传感器信息融合 自校正融合 偏差补偿最小二乘法 收敛性 动态误差系统分析方法 KALMAN滤波器 Multisensor information fusion, self-tuning fusion, bias compensated least-squares (BCRLS) method, convergence, dynamic error system analysis (DESA) method, Kalman filter
作者简介 陶贵丽黑龙江大学自动化系博士研究生.2006年获得黑龙江大学电子工程学院硕士学位.主要研究方向为多传感器信息融合,信号处耻.E—mail:dengzilihlju@yahoo.com.cn 邓自立黑龙江大学自动化系教授.主要研究方向为最优和自校正滤波,状态估计,多传感器信息融合和信号处理.本文通信作者.E—mail:dzl@hlju.edu.cn
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