Long-range photon-efficient 3D imaging without range ambiguity.

Area of Science:

• Photonics
• Remote Sensing
• Computer Vision

Background:

• Single-photon light detection and ranging (LiDAR) is crucial for applications like remote sensing and target recognition.
• Conventional LiDAR systems face limitations in maximum unambiguous distance due to pulsed laser repetition rates.
• Existing methods often rely on depth maps for relative distance measurements, lacking absolute range information.

Purpose of the Study:

• To develop a photon-efficient 3D imaging framework for LiDAR that enables high laser pulse repetition rates.
• To address and eliminate range ambiguity in long-range depth imaging.
• To demonstrate the capability of reconstructing absolute depth maps with minimal photon counts.

Main Methods:

• Proposed a novel 3D imaging framework utilizing photon-efficient techniques.
• Employed a method that uses information from neighboring pixels to reconstruct absolute depth.
• Operated with a single laser period per pixel for enhanced efficiency.

Main Results:

• Successfully demonstrated absolute depth map recovery for scenes ranging from 2.2 km to 13.8 km.
• Achieved this with a low photon budget of approximately 1.41 signal photons per pixel.
• Showcased real-time imaging of absolute distances for moving targets.

Conclusions:

• The developed framework effectively overcomes range ambiguity in long-range LiDAR.
• This photon-efficient approach significantly enhances depth imaging capabilities.
• The system is capable of real-time 3D imaging of dynamic scenes at extended ranges.