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LiDAR (Light Detection and Ranging) is an active remote sensing technology that can accurately and quickly acquire the three-dimensional spatial information of objects. Compared with traditional linear-mode LiDAR, single-photon LiDAR, especially those based on Single-Photon Avalanche Diodes (SPAD), represents an emerging technology with high temporal resolution, high sensitivity, and ease of integration. Due to its unique technological advantages in capturing weak signals and high-precision 3D imaging, it is widely applied in military, aerospace, and autonomous driving fields. In recent years, the continuous development of SPAD detectors has driven the vigorous development and rapid performance improvement of various single-photon LiDAR systems. Furthermore, the single-photon imaging algorithm has evolved from single-point signal processing to array image reconstruction. By exploring the spatiotemporal correlation between pixels, it can accurately restore the depth information carried by weak signals from high background noise. The introduction of deep-learning-based approaches with single-photon imaging prior knowledge has also become one of the current research hotspots. Meanwhile, thanks to powerful imaging algorithms, advanced optomechanical structures, and efficient system designs, they have significantly improved detection accuracy and speed and promoted the application scope of single-photon imaging systems from traditional satellite and airborne applications to vehicle-mounted and consumer electronics fields.
This article focuses on LiDAR technology based on SPAD. Starting from the basic principles, it introduces single-photon LiDAR technology and three typical technical systems, including pulse accumulation time-of-flight technology, coded modulation time-of-flight technology, and chirp modulation coherent detection technology. Based on this, the article highlights SPAD detectors, illustrates the research progress of Si SPAD and InGaAs/InP SPAD, and discusses classical imaging algorithms and typical prior assumptions. Moreover, this review looks back on the current development of single-photon LiDAR in long-distance detection, complex scene sensing, satellite/airborne mapping remote sensing, intelligent driving navigation and obstacle avoidance, and consumer electronics 3D perception, organizing typical systems in different application fields and platforms. Finally, based on current research hotspots and pain points, this article summarizes the main development trends of single-photon detection technology in detectors, imaging algorithms, system integration, and application fields. Of course, single-photon LiDAR also faces challenges such as distance ambiguity and pile-up effects. Therefore, in the design of single-photon LiDAR systems, adopting the concept of computational imaging based on application needs and jointly optimizing the system architecture, optical transmission and reception system, and 3D imaging algorithms might be a beneficial approach. It is hoped that this paper can provide some references for readers to understand the development and design of single-photon LiDAR systems.
The principle of pulse accumulation single photon detection
(a) Results of 3D imaging for a car at 330 m by Buller et al; (b) Results of 3D imaging for a human model at 325 m by Buller et al[14]
Coded modulation of random coding single photon detection technique[16]
Chaos single photon detection system[21]
Chirped modulation single-photon detection principle [16]
(a) Working principle diagram of avalanche photodiode[33]; (b) The typical PDE variation curve of Si SPAD with wavelength[34]
Point cloud before and after data processing for the SPL100
Imaging algorithm effect diagrams of chirp modulated single-photon LiDAR[61]. (a) Accurate depth map of the target scene “Art”; (b) Performance comparisons of different methods with various conditions; (c) Photon efficiency of different approaches
Reconstruction results of the method proposed by Lindell et al[64]
Results of single photon for long-distance detection at 21 km[70]. (a) Photograph of targets and its location in the map; (b) Histogram of return photons from the target
Imaging system and results of single photon for long-distance detection at 201.5 km[11]. (a) Imaging system for long-distance detection at 201.5 km; (b) Photograph of the target; (c) Results of the algorithm proposed by Lindell; (d) Reconstructed 3D profile
A single photon system for underwater detection[78]
(a) Comparison of imaging results with smog[81]; (b) The single photon imaging system with 64×64 InGaAs SPAD detectors[84]
The reconstruction results of the PCE-Net[87]
ATLAS system architecture and results for glacier height measurement by ATLAS[89]. (a) ATLAS system architecture; (b) Results for glacier height measurement by ATLAS
The Leica SPL100 system and terrain features acquired by the SPL100[57]. (a) The Leica SPL100 system; (b) Results reconstructed by the SPL100
(a) Performance metrics and imaging results of ZVISION EZ6; (b) The result of 3D imaging by iPhone 12 Pro