Unified Fast Suboptimal Fixed-Interval White Noise Wiener Smoothing Algorithm
统一的快速次优固定区间白噪声Wiener平滑算法

For the discrete stochastic control systems with correlated noises, using the Kalman filtering method, based on the CARMA innovation model, a unified optimal fixed-interval white noise recursive Wiener smoother is derived. It contains high degree polynomial matrices with coefficient matrices exponentially decaying to zero. Further, by the truncation method, the corresponding fast suboptimal fixed-interval white noise Wiener smoothing algorithm is presented, which obviously reduces the computational burden. The error formula of the smoother and the formula of selecting the truncated index are given. A simulation example for Bernoulli-Gaussian white noise shows the effectiveness of the proposed results.