自校正集中式融合信息滤波器  

Self-tuning Centralized Fusion Information Filter

作　　者：关学慧[1] 邓自立[1] 石莹[1] 

机构地区：[1]黑龙江大学自动化系,哈尔滨150080

出　　处：《科学技术与工程》2010年第2期372-376,共5页Science Technology and Engineering

基　　金：国家自然科学基金(60874063);黑龙江省教育厅科学技术项目(11521124);黑龙江省电子工程重点实验室项目(DZZD2006-16)资助

摘　　要：对于带未知噪声系统和不相关噪声的多传感器随机系统,将基于相关方法得到的噪声方差带入到集中式融合最有信息滤波器,提出自校正集中式融合信息滤波器。同基于Riccatia方程的集中式融合Kalman滤波器相比,它避免了计算高维矩阵的逆,从而减少了计算负担。应用动态误差分析方法,证明了自校正集中式融合信息滤波器以概率1收敛于最优集中式融合信息滤波器,因而具有全局渐进最优性。一个带3传感器跟踪系统的实例说明其有效性。For the multisensor systems with uncorrelated noises, and with unkonw noise varaies, substituting the information fusion noise variance setimators based on the correlation method into the centralized fusion optimal information filter. A self-turning centralized fusion information filter is presenced compared with the self- turning centralized fusion Kalman filter based on the Riccati equation. It can be avoid to compute the inverse matrix with high dimension,so that the calculation hurden can be reduced significantly. Applying of the dynamic error-system analtsis（DESA） metod,it is proved that it converges to the centralixed fusion optimal informa-tion filter, so that it has asymptotical globale optimality. A simultation example for target tracking system with 3 sensor shows its effectiveness

关 键 词：集中式融合 信息矩阵方程 自校正信息滤波器 相关方法 动态误差分析方法 

分 类 号：O211.64[理学—概率论与数理统计]