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 (roliverar@uaz.edu.mx), Reynel Olivera (reynel@uaz.edu.mx), Osbaldo Vite (osvichz@uaz.edu.mx), Hamurabi Gamboa (hamurabigr@uaz.edu.mx), Miguel Ángel Navarrete (mccnavarrete@gmail.com), Claudia Angélica Rivera (c.a.riveraromero@uaz.edu.mx)


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

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


Abstract:
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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