Optimal States Estimation of an LTI System using the Unbiased FIR Filter

Author

Olivera, Roberto ; Olivera, Reynel ; Vite, Osbaldo ; Gamboa, Hamurabi ; Navarrete, Miguel Angel ; Rivera, Claudia Angelica

Author_Institution

Univ. Autonoma de Zacatecas, Jalpa, Mexico

Volume

13

Issue

3

fYear

2015

fDate

Mar-15

Firstpage

609

Lastpage

612

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 dońt 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).

Keywords

AWGN; FIR filters; Kalman filters; mean square error methods; state estimation; AWGN; Kalman filter; LTI systems; MSE; additive white Gaussian noise; linear time invariant; mean square error; optimal states estimation; unbiased linear FIR filter; unbiased linear finite impulse response filter; Electronic countermeasures; Finite impulse response filters; Instruments; Kalman filters; State estimation; Vectors; FIR filtering; Kalman filter; LTI systems; mean square error; optimal estimation;

fLanguage

English

Journal_Title

Latin America Transactions, IEEE (Revista IEEE America Latina)

Publisher

ieee

ISSN

1548-0992

Type

jour

DOI

10.1109/TLA.2015.7069081

Filename

7069081