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

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.