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

被引：1
|
作者：
Olivera, R. [1 ]
Olivera, R. [1 ]
Vite, O. [1 ]
Gamboa, H. [2 ]
Navarrete, M. A. [1 ]
Rivera, C. A. [1 ]
机构：
[1] Univ Autonoma Zacatecas, Unidad Acad Ingn Elect Jalpa, Jalpa, Zac, Mexico
[2] Univ Autonoma Zacatecas, Unidad Acad Ingn Elect, Jalpa, Zac, Mexico
来源：
IEEE LATIN AMERICA TRANSACTIONS | 2015年 / 13卷 / 03期
关键词：
LTI systems; FIR filtering; optimal estimation; Kalman filter; mean square error; KALMAN;
D O I：
10.1109/TLA.2015.7069081
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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).
引用
收藏
页码：609 / 612
页数：4
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