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Homodyne detection efficiency analysis of coherent lidar based on a hybrid algorithm.

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    Atmospheric turbulence degrades coherent lidar performance. This study proposes a hybrid adaptive optics algorithm combining stochastic parallel gradient descent and simulated annealing to improve homodyne detection efficiency for better lidar systems.

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    Area of Science:

    • Atmospheric optics
    • Optical engineering
    • Remote sensing

    Background:

    • Atmospheric turbulence causes phase variations, degrading coherent lidar homodyne detection efficiency and overall performance.
    • Adaptive optics (AO) systems are crucial for correcting wavefront aberrations induced by atmospheric turbulence.

    Purpose of the Study:

    • To propose and evaluate a novel coherent lidar wavefront correction technique.
    • To enhance homodyne detection efficiency in coherent lidar systems using adaptive optics.

    Main Methods:

    • Theoretical analysis of coherent lidar wavefront aberrations.
    • Development of a hybrid algorithm integrating Stochastic Parallel Gradient Descent (SPGD) and Simulated Annealing (SA).
    • Simulation-based verification of the proposed hybrid AO algorithm.

    Main Results:

    • The hybrid SPGD-SA algorithm significantly improves homodyne detection efficiency in coherent lidar.
    • Simulation results demonstrate the algorithm's fast convergence speed.
    • The proposed method exhibits strong wavefront aberration correction capabilities.

    Conclusions:

    • The hybrid SPGD-SA algorithm offers an effective solution for coherent lidar wavefront correction.
    • This technique provides a valuable reference for designing advanced coherent lidar adaptive optics systems.