Dai Chen, Ye Wen-Long, Yu Chao, Huang Xin, Li Zheng-Ping, Xu Feihu
Opt Lett. 2023 Mar 15;48(6):1542-1545. doi: 10.1364/OL.485127.
Single-photon light detection and ranging (LiDAR) has broad applications ranging from remote sensing to target recognition. In most cases, however, the repetition period of the pulsed laser limits the maximum distance that can be unambiguously determined. The relative distances are normally obtained using a depth map. Here, we propose and demonstrate a photon-efficient three-dimensional (3D) imaging framework which permits the operation of high laser pulse repetition rates for long-range depth imaging without range ambiguity. Our approach uses only one laser period per pixel and borrows the information from neighboring pixels to reconstruct the absolute depth map of the scene. We demonstrate the absolute depth map recovery at ranges between 2.2 km and 13.8 km using ∼1.41 signal photons per pixel. We also show the capability to image the absolute distances of moving targets in real time.
单光子光探测与测距（LiDAR）在从遥感到目标识别等广泛领域都有应用。然而，在大多数情况下，脉冲激光的重复周期限制了能够明确确定的最大距离。相对距离通常通过深度图来获取。在此，我们提出并演示了一种光子高效的三维（3D）成像框架，该框架允许在无距离模糊的情况下以高激光脉冲重复率进行远距离深度成像。我们的方法每个像素仅使用一个激光周期，并从相邻像素借用信息来重建场景的绝对深度图。我们展示了在2.2千米至13.8千米的范围内，每个像素使用约1.41个信号光子时绝对深度图的恢复情况。我们还展示了实时成像移动目标绝对距离的能力。
