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The Generation of Higher-order Laguerre-Gauss Optical Beams for High-precision Interferometry
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A Compensation Method for Nonlinearity Errors in Optical Interferometry
Yanlu Li1,2, Emiel Dieussaert1,2
1Photonics Research Group, Ghent University-Imec, Technologiepark-Zwijnaarde 126, 9052 Ghent, Belgium.
Sensors (Basel, Switzerland)
|September 28, 2023
Summary
This study introduces a novel method to correct nonlinearities in optical coherent detection using only demodulated data. This technique accurately compensates for system distortions without needing raw measurements, improving sensing applications.
Area of Science:
- Optics and Photonics
- Sensing Technology
- Signal Processing
Background:
- Optical coherent detection is crucial for sensitive applications but suffers from nonlinearities.
- Existing nonlinear compensation methods often require raw data, limiting their use with processed outputs.
- Demodulated data presents a challenge for accurate interpretation due to signal distortions.
Purpose of the Study:
- To develop a nonlinearity compensation method applicable to demodulated data.
- To address 1st and 2nd-order nonlinearities in homodyne and heterodyne systems.
- To provide a practical solution for systems where raw data is inaccessible.
Main Methods:
- Signal segmentation and baseline fitting to isolate distortions.
- Averaging distortion shapes for accurate parameter retrieval.
- Application to both homodyne and heterodyne optical coherent detection systems.
Main Results:
- Simulations demonstrate effective reduction of nonlinearity-induced deviations without raw data.
- Experimental validation on a silicon-photonics homodyne laser Doppler vibrometer.
- Performance comparable to the established Heydemann correction method.
Conclusions:
- The proposed method offers a viable solution for nonlinearity compensation using only demodulated data.
- This approach enhances the accuracy and applicability of optical coherent detection systems.
- It provides a practical alternative for real-world sensing scenarios with limited data access.
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