Statistical model for fading return signals in coherent lidars.

Area of Science:

• Atmospheric optics
• Optical remote sensing
• Statistical physics

Background:

• Coherent lidar systems rely on accurate signal modeling.
• Atmospheric turbulence and target speckle significantly impact signal quality.
• Understanding these effects is crucial for reliable atmospheric measurements.

Purpose of the Study:

• To develop a statistical model for coherent lidar return signals.
• To analyze the influence of atmospheric turbulence and target speckle on signal-to-noise ratio.
• To investigate the impact of receiver parameters and wavefront compensation.

Main Methods:

• Derivation of a statistical model from atmospheric scattering and propagation principles.
• Development of a three-parameter probability distribution for signal-to-noise ratio.
• Exact expression derivation for lidar fading statistical moments.

Main Results:

• A comprehensive model for coherent lidar signal statistics under turbulence and speckle.
• Quantification of signal-to-noise ratio variations.
• Evaluation of parameters like receiver aperture, speckle area, and mode compensation.

Conclusions:

• The derived model provides accurate predictions for coherent lidar signal behavior.
• The study highlights the importance of accounting for atmospheric effects and receiver characteristics.
• Findings aid in optimizing lidar system design and data interpretation for atmospheric studies.