带相关噪声广义系统降阶滤波器设计

Design of Reduced-order Filter for Descriptor Systems with Correlated Noises

基于广义系统典范型分解,应用射影理论,对带相关噪声的广义离散随机线性系统,通过将带相关噪声系统转化为带独立噪声系统给出一种新的递推降阶滤波器。它能减小计算负担,便于实时应用。与以往文献报道带独立噪声广义系统降阶滤波器相比,所提出的降阶滤波器多了一个当前时刻的增益项。仿真例子说明了其有效性。

Using projection theory and a decomposition in canonical form, a new recursive reduced-order filter for descriptor discrete-time stochastic linear systems with correlated noises is given by transferring system with correlated noised to that with independent noises. It can reduce the computational burden, and is suitable for real-time applications. posed Compared with redured-order filter for descriptor systems with independent noises in exsting literature, the proreduced-order filter has on additional gain at current time. Simulation example proves the effectiveness,