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Phase gradient algorithm method for three-dimensional holographic ladar imaging.

Jason W Stafford, Bradley D Duncan, David J Rabb

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    |July 14, 2016
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    This study introduces a phase gradient algorithm (PGA) for 3D holographic ladar, improving range compression by correcting phase aberrations between frequency samples. The modified PGA shows substantial improvements in laboratory experiments.

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    Area of Science:

    • Optics and Photonics
    • Remote Sensing
    • Signal Processing

    Background:

    • Three-dimensional (3D) holographic ladar utilizes digital holography with frequency diversity for range resolution.
    • A significant challenge is the presence of differential phase aberrations between non-simultaneously recorded frequency samples, hindering range compression.

    Purpose of the Study:

    • To adapt phase gradient algorithms (PGA) for 3D holographic ladar data.
    • To address phase aberrations across multiple temporal frequency samples for improved range compression.

    Main Methods:

    • Development of modality-specific steps for applying PGA to 3D holographic ladar data.
    • Application of modified PGA for phase correction across frequency samples.
    • Analytical description of the PGA estimator's maximum entropy saturation behavior.

    Main Results:

    • Substantial improvement in range compression demonstrated via laboratory experiments.
    • The modified PGA technique effectively corrects phase aberrations.
    • The PGA estimator is shown to be efficient for 3D holographic ladar applications.

    Conclusions:

    • The adapted PGA is a viable and effective method for enhancing range compression in 3D holographic ladar.
    • The efficiency and analytical behavior of the PGA estimator are confirmed for this application.