Signal tracking approach for phase estimation in digital holographic interferometry.

Area of Science:

• Optics and Photonics
• Signal Processing
• Metrology

Background:

• Digital holographic interferometry (DHI) is crucial for precise measurements.
• Phase estimation in DHI is often challenged by noise and rapid variations.
• Existing methods like unwrapping algorithms have limitations in noisy environments.

Purpose of the Study:

• To propose a novel signal tracking approach for phase estimation in DHI.
• To utilize an unscented Kalman filter (UKF) for improved phase estimation.
• To address limitations of conventional phase estimation techniques.

Main Methods:

• Developed a state-space model inspired by Taylor series expansion for the process model.
• Employed polar to Cartesian conversion as the measurement model within the UKF framework.
• Validated the approach using both simulated data and experimental holographic data.

Main Results:

• The proposed UKF-based signal tracking method demonstrates superior performance compared to existing techniques.
• Outperformance is particularly significant at low signal-to-noise ratio (SNR) values (0-20 dB).
• Effective estimation of rapidly varying phases with high dynamic range in noisy conditions was shown.

Conclusions:

• The novel signal tracking approach using UKF offers a robust solution for phase estimation in DHI.
• This method is particularly advantageous for applications involving significant noise and dynamic phase changes.
• The approach provides a valuable alternative to traditional phase unwrapping and approximation methods.