A photon-number-resolving LiDAR approach and an active photon-number-filtering algorithm are proposed and demonstrated.This opens a new avenue for the development of single-photon LiDAR and relevant techniques to scie...A photon-number-resolving LiDAR approach and an active photon-number-filtering algorithm are proposed and demonstrated.This opens a new avenue for the development of single-photon LiDAR and relevant techniques to scientific study and real-world applications.展开更多
Quantum-inspired imaging techniques have been proven to be effective for LiDAR with the advances of single photon detectors and computational algorithms.However,due to the disturbance of background noise and the varie...Quantum-inspired imaging techniques have been proven to be effective for LiDAR with the advances of single photon detectors and computational algorithms.However,due to the disturbance of background noise and the varies of signal in outdoor environment,the performance of LiDAR is still far from its ultimate limit set by the quantum fluctuations of coherent probe light.In this work,we propose and demonstrate a LiDAR from the detection perspective for approaching the standard quantum-limited performance.The photon numbers of echo signals are recorded by a photon-number-resolving detector and applied to overcome heavy background noise through an active photon number filter in the LiDAR.It can approach the standard quantum limit in intensity estimation in a wide photon-flux range,and achieve a Fisher information of only 0.04 dB less than the quantum Fisher information when the mean signal photon number is 10.Experimentally,a noise-free target reconstruction and imaging is demonstrated in the daytime by the proposed LiDAR.It also performs better in reflectivity resolution when taking only 1/1000 of the measurements based on on/off detection.This work provides a fundamental strategy for constructing a LiDAR to quickly extract targets and identify materials in complex environments,which is important for intelligent agents such as autonomous vehicles.展开更多
文摘A photon-number-resolving LiDAR approach and an active photon-number-filtering algorithm are proposed and demonstrated.This opens a new avenue for the development of single-photon LiDAR and relevant techniques to scientific study and real-world applications.
基金supported by Frontier Technologies R&D Program of Jiangsu(No.BF2024058)the National Key Research and Development Program of China(No.2023YFC2205802)+4 种基金the Key-Area Research and Development Program of Guangdong Province(2020B0303020001)National Natural Science Foundation of China(No.12461160276)the Innovation Program for Quantum Science and Technology(No.2021ZD0303401)the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)the Jiangsu Provincial Key Laboratory of Advanced Manipulating Technique of Electromagnetic Waves.
文摘Quantum-inspired imaging techniques have been proven to be effective for LiDAR with the advances of single photon detectors and computational algorithms.However,due to the disturbance of background noise and the varies of signal in outdoor environment,the performance of LiDAR is still far from its ultimate limit set by the quantum fluctuations of coherent probe light.In this work,we propose and demonstrate a LiDAR from the detection perspective for approaching the standard quantum-limited performance.The photon numbers of echo signals are recorded by a photon-number-resolving detector and applied to overcome heavy background noise through an active photon number filter in the LiDAR.It can approach the standard quantum limit in intensity estimation in a wide photon-flux range,and achieve a Fisher information of only 0.04 dB less than the quantum Fisher information when the mean signal photon number is 10.Experimentally,a noise-free target reconstruction and imaging is demonstrated in the daytime by the proposed LiDAR.It also performs better in reflectivity resolution when taking only 1/1000 of the measurements based on on/off detection.This work provides a fundamental strategy for constructing a LiDAR to quickly extract targets and identify materials in complex environments,which is important for intelligent agents such as autonomous vehicles.
