Imaging algorithm of dual-parameter estimation through smoke using Gm-APD lidar

ZHANG Yinbo; LI Haoyang; SUN Jianfeng; LI Sining; JIANG Peng; HOU Yue; ZHANG Hailong

doi:10.37188/OPE.20223019.2370

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Imaging algorithm of dual-parameter estimation through smoke using Gm-APD lidar

Information Sciences | 更新时间：2022-10-24

- Imaging algorithm of dual-parameter estimation through smoke using Gm-APD lidar
- Optics and Precision Engineering Vol. 30, Issue 19, Pages: 2370-2378(2022)
- 作者机构：
  
  1.哈尔滨工业大学光电子技术研究所可调谐（气体）激光技术重点实验室，黑龙江哈尔滨 150001
  2.复杂系统控制与智能协同技术重点实验室，北京 100074
- 作者简介：
  
  E-mail： sjf@hit.edu.cn
- 基金信息：
- DOI：10.37188/OPE.20223019.2370
  CLC： TN958.98
- Received：02 June 2022，
  
  Revised：01 August 2022，
  
  Published：10 October 2022
- 稿件说明：
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张银波,李昊阳,孙剑峰等.Gm-APD激光雷达的双参量估计透烟雾成像算法[J].光学精密工程,2022,30(19):2370-2378.

ZHANG Yinbo,LI Haoyang,SUN Jianfeng,et al.Imaging algorithm of dual-parameter estimation through smoke using Gm-APD lidar[J].Optics and Precision Engineering,2022,30(19):2370-2378.
张银波,李昊阳,孙剑峰等.Gm-APD激光雷达的双参量估计透烟雾成像算法[J].光学精密工程,2022,30(19):2370-2378. DOI： 10.37188/OPE.20223019.2370.

ZHANG Yinbo,LI Haoyang,SUN Jianfeng,et al.Imaging algorithm of dual-parameter estimation through smoke using Gm-APD lidar[J].Optics and Precision Engineering,2022,30(19):2370-2378. DOI： 10.37188/OPE.20223019.2370.

摘要

利用Gm-APD （Geiger mode avalanche photon diode）激光雷达对浓密烟雾背后的目标进行成像时，烟雾对激光的强后向散射和吸收能力，严重限制了传统算法对淹没在烟雾信号中目标信号的提取能力。提出了一种基于双参量估计的Gm-APD激光雷达透烟雾成像算法，介绍了基于Gm-APD激光雷达的触发模型和根据探测概率求解实际接收回波信号的原理，并且基于光子与烟雾粒子的碰撞理论和Mie散射理论，详细推导了Gamma模型两个参数的物理关系。根据推导的关系式提出了一种双参量估计算法，该算法考虑了如何精确估计

，

两个参数。最后，开展了仿真和室内透雾实验，利用仿真实验检验

，

关系式的正确性，利用室内实验验证提出算法的透雾成像能力。实验结果表明，相较于传统算法，本文提出算法重构图像的目标复原度提升了73%，结构相似性提升了0.228 9。该研究有效提升了Gm-APD激光雷达在烟雾环境中的目标感知能力。

Abstract

When Geiger mode avalanche photo diode （Gm-APD） lidar is used to image targets obscured by dense smoke， the strong backscattering and absorption of laser light by the smoke severely limit the ability of traditional algorithms in extracting the target signal hidden in the smoke signal. To this end， we propose a Gm-APD lidar imaging algorithm based on dual-parameter estimation for imaging in smoke environments. First， this paper introduces a trigger model based on Gm-APD lidar and describes the principle for solving the actual received echo signal based on the detection probability. In addition， based on the collision theory of photons and smoke particles， as well as the Mie scattering theory， the physical relationship between the two parameters of the gamma model is derived. Second， a dual-parameter estimation algorithm is proposed based on the derived relationship， which considers approaches to accurately estimate μ and k. Finally， simulation and indoor experiments are conducted. The correctness of the relationship between μ and k is verified based on these simulation experiments， and the imaging ability of the proposed algorithm in the presence of smoke is verified through indoor experiments. The experimental results reveal that compared with traditional algorithms， the target recovery of the image reconstructed by the proposed algorithm increases by 73%， and the structural similarity increases by 0.228 9. Thus， this study effectively improves the target perception ability of Gm-APD lidar in smoke environments.

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references

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