Limits to the information gain from lidar measurements

Area of Science:

• Atmospheric Science
• Optical Remote Sensing

Background:

• Lidar remote sensing relies on analyzing return signals to understand target characteristics.
• Quantifying the information content of lidar measurements is crucial for optimizing data acquisition and interpretation.

Purpose of the Study:

• To define and quantify the information content of lidar observations using Shannon's mutual information.
• To mathematically describe the capacity of lidar estimates to represent target properties.
• To derive analytical formulas for information gain in specific lidar systems.

Main Methods:

• Definition of Shannon's mutual information applied to lidar observations.
• Mathematical formulation of the information capacity of lidar estimates.
• Derivation of analytical formulas for heterodyne Doppler lidars.

Main Results:

• Established a framework for quantifying information content in lidar measurements.
• Developed mathematical expressions for the representational capacity of lidar estimates.
• Derived simple analytical formulas for information gain in mean-frequency estimates from heterodyne Doppler lidars.

Conclusions:

• The study provides a theoretical basis for understanding information gain in lidar remote sensing.
• The derived formulas offer practical tools for optimizing heterodyne Doppler lidar system design and data analysis.
• This work advances the quantitative understanding of information extraction in optical remote sensing.