Joint estimation of self-mixing interferometry parameters and displacement reconstruction based on local...

Area of Science:

• Optics and Photonics
• Metrology and Measurement

Background:

• Self-mixing interferometry (SMI) is crucial for displacement sensing.
• Estimating key parameters like optical feedback and linewidth enhancement factors from noisy self-mixing signals (SMSs) is difficult.
• Existing normalization methods for SMSs are complex and can distort signal information, leading to inaccurate parameter estimation and displacement reconstruction.

Purpose of the Study:

• To introduce a novel, noise-resilient normalization method for self-mixing signals.
• To enable simpler and more accurate estimation of self-mixing interferometry parameters.
• To improve displacement reconstruction in the presence of noise, particularly speckle.

Main Methods:

• Development of a "local normalization" technique based on an analytic relation.
• Application of the method to self-mixing signals affected by noise, including speckle.
• Validation of the method in moderate and strong feedback regimes.

Main Results:

• The proposed local normalization method simplifies parameter estimation and displacement retrieval.
• The method demonstrates high noise-proof capabilities, especially against speckle noise.
• Accurate parameter estimation and displacement reconstruction are achieved without signal distortion.

Conclusions:

• The local normalization method offers a significant improvement over existing techniques for self-mixing interferometry.
• This method facilitates the development of low-cost, high-resolution (approx. 40 nm) self-mixing displacement sensors.
• The simplicity and accuracy of the local normalization method make it a valuable tool for practical applications.