Sub‐Diffraction Limited Single‐Photon LiDAR with Optimized Confocal Super‐Oscillatory Illumination

Abstract Object detection, recognition, and identification impose stringent requirements on the imaging resolution of light detection and ranging (LiDAR) systems. The ability of LiDAR to resolve objects is constrained by the Abbe‐Rayleigh diffraction limit due to the wave nature of light. Superoscillation, as a far‐field super‐resolution technique, theoretically allows for the generation of arbitrarily small light spots. However, its practical implementation is primarily validated within the microscopic domain because of the weak super‐diffractive information and strong sidelobe noise. Consequently, its application in far‐field super‐diffractive imaging with light waves remains insufficiently explored. In this study, the first functional prototype is presented for super‐resolution imaging using super‐oscillatory illumination in LiDAR. By utilizing a specifically engineered super‐oscillatory light field with confocal illumination, super‐resolution imaging of a target at a distance of 20 meters is achieved. This work offers a promising approach for achieving super‐resolution in active 3D imaging.

Authors

Institutions

Publication Details

Journal
Laser & Photonics Review
Published
2025-04-15
DOI
https://doi.org/10.1002/lpor.202401837
Citations
8
Primary Topic
Advanced Optical Sensing Technologies
Type
article
Field-Weighted Citation Impact
9.53

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Sub‐Diffraction Limited Single‐Photon LiDAR with Optimized Confocal Super‐Oscillatory Illumination

Mingbo Pu, Yuanjian Huang, Yinghui Guo, Nan Chi et al.
8 citations
Laser & Photonics Review
Advanced Optical Sensing Technologies
9.53
article

Sub‐Diffraction Limited Single‐Photon LiDAR with Optimized Confocal Super‐Oscillatory Illumination

Mingbo Pu, Yuanjian Huang, Yinghui Guo, Nan Chi, Runzhe Zhang, Qi Zhang, Fei Zhang, Mingfeng Xu, Xiaoyin Li, Hengshuo Guo, Xiangang Luo
article en
8 citations

Abstract

Abstract Object detection, recognition, and identification impose stringent requirements on the imaging resolution of light detection and ranging (LiDAR) systems. The ability of LiDAR to resolve objects is constrained by the Abbe‐Rayleigh diffraction limit due to the wave nature of light. Superoscillation, as a far‐field super‐resolution technique, theoretically allows for the generation of arbitrarily small light spots. However, its practical implementation is primarily validated within the microscopic domain because of the weak super‐diffractive information and strong sidelobe noise. Consequently, its application in far‐field super‐diffractive imaging with light waves remains insufficiently explored. In this study, the first functional prototype is presented for super‐resolution imaging using super‐oscillatory illumination in LiDAR. By utilizing a specifically engineered super‐oscillatory light field with confocal illumination, super‐resolution imaging of a target at a distance of 20 meters is achieved. This work offers a promising approach for achieving super‐resolution in active 3D imaging.

Laser & Photonics ReviewVol. 19(15)
Chinese Academy of Sciences (CN), Fudan University (CN), Institute of Optics and Electronics, Chinese Academy of Sciences (CN), Sichuan Research Center of New Materials (CN), University of Chinese Academy of Sciences (CN)
National Natural Science Foundation of China, Natural Science Foundation of Sichuan Province, National Key Research and Development Program of China
Openalex Percentile: Top 2%
Advanced Optical Sensing Technologies
9.53
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.