General and unified white noise estimation approachbased on Kalman filtering
基于Kalman滤波的通用和统一的白噪声估计方法

By the projection theory,general and unified white noise estimation approach is proposed based on Kalman filtering.It can solve the white noise filtering,smoothing and prediction problems in a unified framework for linear discrete time_varying stochastic control systems with correlated noises having non_zero mean.The input white noise estimators and measurement white noise estimators,optimal and steady_state white noise estimators,fixed point,fixed lag and fixed interval white noise smoothers,and white noise innovation filter and Wiener filter are presented.The approach can be applied to signal processing in oil seismic exploration and state estimation,and provide a new way to solve the signal and state estimation problems.The simulation example for Bernoulli_Gaussian white noise estimators shows its effectiveness.