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Algorithm to overcome atmospheric phase errors in SAL data.

Randy S Depoy, Arnab K Shaw

    Applied Optics
    |April 1, 2020
    PubMed
    Summary
    This summary is machine-generated.

    Synthetic aperture ladar (SAL) image quality degrades due to atmospheric turbulence. Model-based reconstruction with error correction effectively mitigates these effects, restoring high-resolution SAL imagery.

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    Area of Science:

    • Remote Sensing
    • Optical Engineering
    • Atmospheric Optics

    Background:

    • Synthetic aperture ladar (SAL) offers high-resolution imaging from long distances.
    • Atmospheric turbulence introduces phase errors, degrading SAL image quality and resolution.
    • Existing reconstruction methods struggle with spatially variant atmospheric effects.

    Purpose of the Study:

    • To evaluate model-based reconstruction algorithms for mitigating atmospheric turbulence in SAL.
    • To investigate the effectiveness of different model error correction techniques.
    • To restore image quality and resolution in SAL imagery corrupted by atmospheric phase perturbations.

    Main Methods:

    • Exploration of model-based reconstruction algorithms.
    • Implementation of spatially invariant, spatially variant, and model-based atmospheric phase error corrections.
    • Performance quantification using an atmospheric ray-trace simulation.

    Main Results:

    • Model-based reconstruction with error correction significantly mitigates turbulence effects.
    • Spatially variant and model-based error corrections show improved performance over spatially invariant methods.
    • Restoration of resolution and contrast in simulated SAL imagery.

    Conclusions:

    • Model-based reconstruction algorithms are effective for correcting atmospheric turbulence in SAL.
    • Advanced error correction strategies are crucial for high-fidelity SAL imaging in turbulent atmospheres.
    • This work provides a pathway for improved SAL performance in real-world conditions.