Recursive Optimal Finite Impulse Response Filter and Its Application to Adaptive Estimation

In this paper, the recursive form of an optimal finite impulse response filter is proposed for discrete time-varying state-space models. The derived by employing horizon Kalman filtering with optimally estimated initial conditions. state and its error covariance on are using recent measurements, in sense maximum likelihood estimation, then initiating filter. optimality unbiasedness proved comparison conventional batch form. Moreover, adaptive FIR also applying estimation scheme to as application. To evaluate performance algorithms, a computer simulation performed compare filters gas turbine aircraft engine model.