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GM-APD lidar reconstruction algorithm with few frames based on sample function

delete2025-09-11
delete0
PRE
AI
Z
Zhou Shi
J
Jianfeng Sun
D
Dajian Cui *
X
Xin Zhou
H
Hongchao Ni
DOI：10.1016/j.optlastec.2025.113866delete
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摘要

摘要

En 中文
在帧数较少且信背比（SBR）较低的情况下，当盖革模式雪崩光电二极管（GM-APD）激光雷达重构距离图像时，其回波数据的统计形式表现出稀疏性和离散性。光子触发概率分布直方图容易丢失目标峰值，导致难以准确估计目标峰值的位置，从而影响小目标和弱目标的检测。为解决此问题，定义了回波信号的峰值显著性概念，并提出了一种基于样本函数的算法。该算法首先恢复丢失的目标峰值，对目标峰值进行滤波以去除小尖峰，并计算局部峰值的峰值显著性。峰值显著性最大的局部峰值即为目标峰值，从而能够准确估计目标峰值的位置。在自建GM-APD激光雷达探测成像平台上的实验结果表明，在SBR = 0.0263的实际场景中，所提算法的三个评价指标均优于SPIRAL算法。目标恢复度（K）比SPIRAL高43%，峰值信噪比（PSNR）提升了9.5 dB，平均绝对误差（MAE）减少了95 bins。这证实了该算法在少帧、低信噪比GM-APD探测成像领域的重要性，并具有广阔的应用前景。

期刊

O
Optics and Laser Technology
IF:
5
论文数:
2.4K
被引数:
3.5W

机构

H
harbin institute of technology
学者数:
8.0W
论文数: 6.6W
被引数: 66
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