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
State Key Laboratory of Quantum Optics Technologies and Devices, Institute of Laser Spectroscopy, Shanxi University, Taiyuan, 030006, China.
Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, 030006, China.
Light Sci Appl. 2025 Jul 14;14(1):244. doi: 10.1038/s41377-025-01878-y.
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 2.05 GHz, 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.
在存在强背景噪声的情况下进行远程无源无人机检测具有挑战性，因为无人机是点状物体，无法通过轮廓检测来识别。在本研究中，我们引入了一种使用量子压缩感知的新型无源单光子动态成像方法。该方法利用光子辐射和检测的固有随机性来构建压缩成像系统。它通过稀疏光子检测捕获点状物体的宽带动态特征，实现高达2.05 GHz的可检测带宽，这明显高于当前的光子计数成像技术。该方法还表现出出色的抗噪声能力，在信背比为1/332的情况下实现了高质量成像。这项技术显著增强了单光子成像在实际应用中的用途。
