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Super-resolution technique for CW lidar using Fourier transform reordering and Richardson-Lucy deconvolution.

Joel F Campbell, Bing Lin, Amin R Nehrir

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    This study introduces an advanced interpolation method for lidar range measurements, significantly enhancing resolution beyond fundamental limits. The technique improves accuracy for applications like cloud and canopy thickness determination.

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    Area of Science:

    • Optics and Photonics
    • Signal Processing
    • Remote Sensing

    Background:

    • High-precision altimetry requires accurate range measurements.
    • Intensity Modulated Continuous Wave (IM-CW) lidar with Binary Phase Shift Keying (BPSK) is used for range profiling.
    • Existing methods face fundamental resolution limits based on bandwidth and bit rate.

    Purpose of the Study:

    • To develop an interpolation method for enhancing range resolution in IM-CW lidar.
    • To overcome the theoretical resolution limits of BPSK modulation.
    • To demonstrate improved accuracy in measuring cloud and tree canopy thicknesses.

    Main Methods:

    • Utilizing cross-correlation between transmitted and received lidar signals.
    • Applying frequency domain reordering to convert repeating synthetic pulses into a single interpolated pulse.
    • Enhancing pulse resolution further with Richardson-Lucy deconvolution.

    Main Results:

    • Achieved enhancement in sampling resolution and pulse width by approximately two orders of magnitude.
    • Successfully broke the fundamental resolution limit for BPSK modulation.
    • Demonstrated effective application in determining cloud and tree canopy thicknesses.

    Conclusions:

    • The described signal processing algorithms significantly enhance lidar range measurement resolution.
    • This technique enables high-precision measurements beyond conventional limitations.
    • The method proves valuable for atmospheric and vegetation profiling applications.