Pre-Processing of Signals Observed from Laser Diode Self-mixing Intereferometries using Neural Networks

Author

Wei, Lu ; Chicharo, Joe ; Yu, Yanguang ; Xi, Jiangtao

Author_Institution

Univ. of Wollongong, Wollongong

fYear

2007

fDate

3-5 Oct. 2007

Firstpage

1

Lastpage

5

Abstract

This paper presents a novel neural network signal interpolation technique in order to eliminate the noise and disturbance associated with the self-mixing signal observed from optical feedback self-mixing interferometry (OFSMI). The proposed technique aims to improve the accuracy for displacement and moving track measurement of a target. The performance of the proposed approach is evaluated by both simulation and experimentation, with simulation revealing a measuring accuracy of lambda/25 for weak feedback and lambda/20 for moderate feed back.

Keywords

interpolation; light interferometry; optical neural nets; semiconductor lasers; signal processing; laser diode; neural network; optical feedback self-mixing interferometry; signal interpolation technique; Diode lasers; Displacement measurement; Laser feedback; Laser modes; Neural networks; Optical feedback; Optical interferometry; Semiconductor lasers; Signal processing; Target tracking; Displacement measurement; optical feedback; self-mixing interferometry; semiconductor lasers;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Signal Processing, 2007. WISP 2007. IEEE International Symposium on

Conference_Location

Alcala de Henares

Print_ISBN

978-1-4244-0830-6

Electronic_ISBN

978-1-4244-0830-6

Type

conf

DOI

10.1109/WISP.2007.4447499

Filename

4447499