An Entropy-Based Anti-Noise Method for Reducing Ranging Error in Photon Counting Lidar.

Area of Science:

• Photon counting lidar
• Optical sensing
• Signal processing

Background:

• Photon counting lidar systems suffer from reduced ranging accuracy due to background noise, especially with weak signals.
• Existing anti-noise techniques are insufficient for scenarios with high background noise and weak signals, leading to significant ranging errors.
• Accurate ranging is critical for long-range detection applications.

Purpose of the Study:

• To propose and validate a novel entropy-based anti-noise method for photon counting lidar.
• To reduce ranging error in photon counting lidar systems operating under high background noise conditions.
• To enhance the robustness of ranging performance in challenging environmental conditions.

Main Methods:

• Definition of photon counting entropy to quantify signal and noise uncertainty.
• Integration of photon counting entropy with a windowing operation to differentiate signal from noise.
• Estimation of time-of-flight using the enhanced signal-to-noise ratio.
• Validation through simulations and experimental analysis.

Main Results:

• The proposed entropy-based method effectively quantifies the uncertainty of photon events.
• Combining photon counting entropy with windowing significantly enhances the distinction between signal and noise.
• The method demonstrates improved anti-noise performance compared to existing approaches.
• Experimental results confirm a substantial reduction in ranging error under high background noise.

Conclusions:

• The developed entropy-based anti-noise method offers a robust solution for improving photon counting lidar ranging accuracy.
• This technique is particularly effective in mitigating the detrimental effects of high background noise.
• The findings pave the way for more reliable long-range detection systems in noisy environments.