Method for self-mixing interference signal analysis based on Kalman filter

Yuyan Zhang; Yutian Wang; Xiaoyuan Luo; Rui Ren

doi:10.1117/12.782957

17 January 2008 Method for self-mixing interference signal analysis based on Kalman filter

Yuyan Zhang, Yutian Wang, Xiaoyuan Luo, Rui Ren

Proceedings Volume 6723, 3rd International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test and Measurement Technology and Equipment; 67230O (2008) https://doi.org/10.1117/12.782957
Event: 3rd International Symposium on Advanced Optical Manufacturing and Testing Technologies: Large Mirrors and Telescopes, 2007, Chengdu, China

Abstract

In this paper, a new signal processing method based on Kalman filter is presented for self-mixing displacement sensor. Based on the approximate linearized model of a LD, the robust Kalman filter is designed for an estimation of system parameters and target displacement. The proposed signal processing algorithm increases the resolution well beyond half-wavelength, without any external optical components, preliminary separate measurements, or target surface preparation. Simulation analysis and experiments have been done to illustrate the validity and the effectiveness of the method. These results show that the displacement estimation is good with little noise and the estimated accuracy of about λ/20 is achievable.

Citation Download Citation

Yuyan Zhang, Yutian Wang, Xiaoyuan Luo, and Rui Ren "Method for self-mixing interference signal analysis based on Kalman filter", Proc. SPIE 6723, 3rd International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test and Measurement Technology and Equipment, 67230O (17 January 2008); https://doi.org/10.1117/12.782957

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available