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High Speed Sub-GHz Spectrometer for Brillouin Scattering Analysis
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Extracting Brillouin frequency shift accurately based on particle swarm optimization and a cross-correlation method.

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    A novel fitting algorithm combining particle swarm optimization (PSO) and cross-correlation method (XCM) enhances Brillouin scattering spectrum analysis. This method significantly reduces errors and improves accuracy in fiber optic sensing systems.

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    Area of Science:

    • Optics
    • Fiber Optics
    • Signal Processing

    Background:

    • Brillouin scattering spectroscopy is crucial for fiber optic sensing.
    • Accurate feature extraction from Brillouin spectra is challenging due to noise and spectral variations.
    • Existing methods like Lorenz fitting and basic XCM have limitations in precision.

    Purpose of the Study:

    • To develop and validate a robust fitting algorithm for accurate Brillouin scattering spectrum feature extraction.
    • To improve demodulation accuracy and reduce spectral analysis errors.
    • To assess the algorithm's performance across diverse spectral conditions and its application in sensing systems.

    Main Methods:

    • A hybrid fitting algorithm integrating Particle Swarm Optimization (PSO) with the Cross-Correlation Method (XCM) was developed.
    • Simulations and experimental setups were employed to validate the proposed PSO-XCM algorithm.
    • Performance was evaluated against traditional Lorenz curve fitting and standalone XCM.

    Main Results:

    • The PSO-XCM algorithm demonstrated high demodulation accuracy across various signal-to-noise ratios, spectral widths, and symmetries.
    • Extraction errors were significantly reduced, achieving up to 99.98% optimization compared to other methods.
    • Fitting degree improved by 98%, with minimal temperature (0.06°C) and Brillouin frequency shift (0.07 MHz) errors in a 10 km BOTDA system.

    Conclusions:

    • The PSO-XCM algorithm offers superior accuracy and robustness for analyzing Brillouin scattering spectra.
    • This advancement is highly suitable for demanding applications like Brillouin optical time domain analysis (BOTDA) sensing.
    • The method provides a reliable approach for precise measurements in long-haul fiber optic sensing.