Estimación Óptima de los Estados de un Sistema LIT Utilizando el Filtro FIR sin Sesgo (Optimal States Estimation of an LTI System using the Unbiased FIR Filter)

Roberto Olivera (, Reynel Olivera (, Osbaldo Vite (, Hamurabi Gamboa (, Miguel Ángel Navarrete (, Claudia Angélica Rivera (

Universidad Autónoma de Zacatecas
This paper appears in: Revista IEEE América Latina

Publication Date: March 2015
Volume: 13,   Issue: 3 
ISSN: 1548-0992

The unbiased linear finite impulse response (FIR) filter and the two-state Kalman filter are investigated in the optimal estimation of the two state (position and velocity) in a linear time invariant (LTI) systems in presence of additive white Gaussian noise (AWGN). In opposite to the Kalman filter, the unbiased linear FIR filter don´t need previous knowledge about noise process, this algorithm only needs two specific parameters: optimal time step and optimal number of the points in the average. We show that both algorithms produce a similar lower mean square error (MSE).

Index Terms:
LTI systems, FIR filtering, optimal estimation, Kalman filter, mean square error.   

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