单量估计法单光子激光透雾成像

Single quantity estimation method for single photon lidar dehazing imaging

传统激光雷达在透雾成像过程中受探测接收灵敏度限制无法提取淹没在强后向散射噪声内的目标信号,难以达到透雾效果。本文提出单量估计法的面阵盖革模式雪崩光电二极管激光雷达透雾成像算法,依据盖革模式触发探测模型,通过对回波光子进行极大似然估计得到后向散射分布,提取目标回波位置,抑制了后向散射噪声,达到透雾成像的目的。搭建了室内激光透雾成像实验平台,获取了不同浓度下的透雾成像数据。实验结果表明,与峰值法和双量估计法相比,单量估计法能最大程度恢复目标像素数,衰减系数为0.11 m-1时,相比峰值法距离信息恢复量提升8.26%,目标复原度降低16.22%;衰减系数为0.86 m-1时,相比峰值法距离信息恢复量提升86.86%,目标复原度提高20.51%;衰减系数为2.37 m-1时,相比峰值法距离信息恢复量提升253.19%,目标复原度提高53.44%。在衰减系数较大时,单量估计法在信号级去雾处理上的目标复原度较高。

Conventional lidar cannot be used to extract a target signal from the strong backscatter noise in fog-penetration imaging because of the inherent detection and reception sensitivity limitations of lidar.Therefore,achieving the fog penetration effect is difficult.To address this problem,a novel single-quantile estimation method was proposed for the fog-penetration imaging algorithm based on Geiger-mode avalanche-photodiode lidar.According to the Geiger-mode trigger detection model,the backscattering distribution was obtained through the maximum likelihood estimation of the echo photon.Fog-penetration imaging was then achieved through subsequent extraction of the target echo position and backscattering noise suppression.The experimental platform of laser fog-penetration imaging was developed,and fog-penetration imaging under various fog conditions were performed.The results revealed that the single-estimation method outperformed the peak and double-estimation methods.When the attenuation coefficient was 0.11 m^(-1),the distance information recovery of the peak method increased by 8.26%and the target recovery degree decreased by 16.22%.When the attenuation coefficient was 0.86 m^(-1),the distance information recovery of the peak method increased by 86.86%,and the target recovery degree increased by 20.51%.When the attenuation coefficient was 2.37 m^(-1),the distance information recovery of the peak method increased by 253.19%,and the target recovery degree increased by 53.44%.A high degree of target restoration was achieved in signal-level dehazing by using the single-quantity estimation method.