Dynamic gate algorithm for multimode fiber Bragg grating sensor systems.

Area of Science:

• Optical sensing
• Signal processing
• Photonics

Background:

• Accurate peak detection is crucial for signal analysis in various sensing applications.
• Conventional algorithms often face limitations in speed, stability, and accuracy, especially in complex signal environments.

Purpose of the Study:

• To introduce a novel dynamic gate algorithm (DGA) for precise and accurate peak detection.
• To evaluate the performance of the DGA in terms of wavelength fit resolution under varying signal-to-noise ratios and peak shapes.

Main Methods:

• Implementation of a dynamic gate algorithm (DGA) utilizing a threshold-determined detection window.
• Application of a center of gravity algorithm with bias compensation for peak analysis.
• Simulations and experimental validation of the DGA's performance.

Main Results:

• The DGA demonstrates fast and robust performance in peak detection.
• The algorithm exhibits superior stability and accuracy compared to conventional methods.
• Analysis shows good wavelength fit resolution across different signal-to-noise ratios and peak shapes.

Conclusions:

• The dynamic gate algorithm (DGA) offers a significant advancement in peak detection technology.
• Its speed, robustness, stability, and accuracy make it highly suitable for real-time sensing applications.
• The DGA is particularly promising for implementation in multimode fiber Bragg grating-based sensing systems.