广义系统降阶Wiener状态平滑器  

Reduced-Order Wiener State Smoother for Descriptor Systems

作　　者：孙书利[1] 孟华[1] 石莹[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》2003年第5期405-407,共3页Science Technology and Engineering

基　　金：国家自然科学基金(69774019);黑龙江省自然科学基金(F01-15)

摘　　要：用Kalman滤波方法,利用典范型分解对线性离散时不变广义随机系统提出了降阶Wiener状态平滑器,可明显减小计算负担,便于实时应用。一个仿真的例子说明了其有效性。Using the Kalman filtering method, applying a decomposition in canonical form, a reduced-order Wiener state smoother is presented for linear discrete time-invariant descriptor stochastic systems, which can obviously reduces the computational burden and is suitable for real time applications. A simulation example shows its effectiveness.

关 键 词：广义系统 KALMAN滤波 线性离散时不变广义随机系统 降阶Wiener状态平滑器 滤波器 

分 类 号：TB535[理学—物理]