自校正观测融合解耦Wiener状态预报器  

Self-tuning Measurement Fusion Decoupled Wiener State Predictor

作　　者：陈红[1] 邓自立[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》2007年第24期6285-6290,共6页Science Technology and Engineering

基　　金：国家自然科学基金(60374026)资助

摘　　要：对于带未知噪声方差和带不同观测阵的多传感器系统,应用现代时间序列分析方法,基于子系统和加权观测融合系统的滑动平均(MA)新息模型的在线辨识,提出了一类自校正加权观测融合解耦Wiener状态预报器。用动态误差系统分析方法,证明了它按实现收敛于当噪声方差已知时的最优加权观测融合解耦Wiener状态预报器,因而它具有渐近全局最优性。一个目标跟踪系统的仿真例子说明了其有效性。For the multisensor systems with unknown noise variances, and with diffrernt measurement matrices, using the modern time series analysis method, based on the on-line identification of the moving average （MA） innovation models of the subsystems and weighted measurement fusion system, a class of the self-tuning weighted measurement fusion decoupled Wiener state predictors is presented. By the it is proved that it converges to the optimal weighted measurement fusion dynamic error system analysis method, decoupled Wiener state predictor with known noise variances in a realization, so that it has asymptotic global optimality. A simulation example for a target tracking system shows its effectiveness.

关 键 词：多传感器信息融合 加权观测融合 自校正解耦融合Wiener状态预报器 收敛性 现代时间序列分析方法 

分 类 号：O211.64[理学—概率论与数理统计]