近日，山西大学肖连团课题组研究了利用宽带量子压缩传感成像进行10公里被动无人机探测。相关论文于2025年7月14日发表在《光：科学与应用》杂志上。

在存在强背景噪声的情况下，远程被动无人机检测具有挑战性，因为它们是点目标，无法通过轮廓检测识别。

研究组介绍了一种新的以量子压缩感知为主题的被动单光子动态成像方法。该方法利用光子辐射和探测的固有随机性来构建压缩成像系统。它通过稀疏光子探测捕捉点目标的宽带动态特征，实现了高达2.05GHz，明显高于当前的光子计数成像技术。该方法还具有优异的抗噪声性能，实现了高质量的成像，信背景比为1/332。该技术显著增强了单光子成像在现实世界中的应用。

附：英文原文

Title: 10-km passive drone detection using broadband quantum compressed sensing imaging

Author: Wu, Shuxiao, Hu, Jianyong, Ge, Jiaqing, Fan, Yanshan, Li, Zhexin, Yang, Liu, Song, Kai, Tian, Jiazhao, Qiao, Zhixing, Feng, Guosheng, Liang, Xilong, Yang, Changgang, Chen, Ruiyun, Qin, Chengbing, Zhang, Guofeng, Xiao, Liantuan, Jia, Suotang

Issue&Volume: 2025-07-14

Abstract: Remote passive drone detection in the presence of strong background noise is challenging, since they are point objects and cannot be recognized by their contour detection. In this study, we introduce a new passive single-photon dynamic imaging method using quantum compressed sensing. This method utilizes the inherent randomness of photon radiation and detection to construct a compressive imaging system. It captures the broadband dynamic features of the point object through sparse photon detection, achieving a detectable bandwidth up to 2.05GHz, which is significantly higher than current photon-counting imaging techniques. The method also shows excellent noise resistance, achieving high-quality imaging with a signal-to-background ratio of 1/332. This technique significantly enhances the use of single-photon imaging in real-world applications.

DOI: 10.1038/s41377-025-01878-y

Source: https://www.nature.com/articles/s41377-025-01878-y