Geometrical compression of lidar return signals

Area of Science:

• Optical remote sensing
• Laser physics

Background:

• Lidar systems are crucial for atmospheric and terrestrial measurements.
• The dynamic range of lidar return signals presents challenges in data acquisition.
• Traditional methods like gain switching have limitations.

Purpose of the Study:

• To analyze the dynamic range of lidar return signals in coaxial geometries.
• To investigate methods for mitigating signal amplitude variations with distance.
• To compare geometric compression with electronic compression techniques.

Main Methods:

• Calculation of lidar return signal dynamic range.
• Analysis of spatial irradiance distribution in the detector plane.
• Evaluation of geometric parameter effects on signal amplitude.
• Comparison with electronic compression methods.

Main Results:

• The z(-2) dependence in the lidar equation can be overcome.
• A near-constant signal amplitude is achievable up to 3 km using geometric compression.
• No signal degradation occurs at larger distances with this method.
• Geometric compression is shown to be superior to electronic methods.

Conclusions:

• Geometric optimization of lidar systems can effectively manage signal dynamic range.
• This approach enhances lidar data quality and simplifies processing.
• Geometric compression presents a novel and efficient alternative to electronic signal compression.