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Photon Counting LIDAR Based on True Random Coding.

Yang Yu1,2, Bo Liu1,2, Zhen Chen1,2

  • 1Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China.

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This summary is machine-generated.

This study introduces a true random coding photon counting LIDAR system using a Geiger-mode avalanche photodiode (Gm-APD) for improved anti-crosstalk and reduced missed detections. Experiments confirm its effectiveness for target detection and offer new insights for LIDAR system development.

Keywords:
LIDARphoton countingtrue random coding

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Area of Science:

  • Optoelectronics
  • Photonics
  • LIDAR Technology

Background:

  • Photon counting LIDAR systems face challenges with crosstalk and missed detections due to limitations in Geiger-mode avalanche photodiode (Gm-APD) count rates.
  • Traditional random coding methods may not fully address these limitations, impacting system performance.

Purpose of the Study:

  • To describe a novel true random coding photon counting LIDAR system.
  • To demonstrate the improved anti-crosstalk capability and reduced missed detection rates of this new system.
  • To evaluate the feasibility and performance of true random sequences in LIDAR applications.

Main Methods:

  • Utilized a Geiger-mode avalanche photodiode (Gm-APD) as a true random sequence signal generator.
  • Developed a true random coding method to enhance system performance.
  • Proposed a simple evaluation model for true random sequence autocorrelation.
  • Conducted experiments to verify system feasibility and explored the influence of various system parameters on detection probability.

Main Results:

  • The true random coding method significantly improves anti-crosstalk capabilities.
  • Missed detection rates, particularly the 1-bit error, are substantially reduced.
  • Experimental verification confirms the feasibility of true random sequences in photon counting LIDAR ranging.
  • The study identified key system parameters affecting detection probability, including echo photon number, pulse count density, sequence length, and noise count.

Conclusions:

  • True random code photon counting LIDAR is an effective method for target detection.
  • The developed system offers a promising solution for mitigating crosstalk in LIDAR.
  • This research provides a new direction for developing advanced anti-crosstalk LIDAR systems.