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摘要:
随着单光子探测器件及技术的快速发展，具有光子级高灵敏度探测能力的单光子激光雷达已成为研究热点，并在遥感测绘、智能驾驶和消费电子等领域发挥日益重要的作用。本文聚焦于采用单光子雪崩光电二极管探测器的激光雷达技术与系统，介绍了脉冲累积、编码调制和啁啾调制三种单光子激光雷达探测原理。考虑到单光子探测器与处理算法的重要性，概述了单光子探测器的发展现状，以及典型的信号处理算法，并梳理了单光子激光雷达在远距离探测、复杂场景探感、星载/机载测绘遥感、智能驾驶导航避障和消费电子3D感知等领域的应用情况和典型系统实例。最后，分析展望了单光子激光雷达技术在器件、算法、系统和应用领域的未来发展趋势及面临的潜在挑战。
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关键词:
- 激光雷达 /
- 信号处理 /
- 光子计数 /
- 单光子雪崩光电二极管
Abstract:With the rapid development of single-photon detectors and technologies, single-photon LiDAR with photon-level sensitivity has become a popular research topic. It plays an increasingly important role in fields such as remote sensing and mapping, intelligent driving, and consumer electronics. This paper focuses on LiDAR technologies and systems employing single-photon avalanche diode detectors, introducing three single-photon LiDAR detection principles: pulse accumulation, coding modulation and chirp modulation. Considering the importance of detectors and algorithms, it outlines the current development status of single-photon detectors and typical processing algorithms. It also reviews the applications and typical systems of single-photon LiDAR in long-distance detection, complex scene sensing, satellite/airborne remote sensing and mapping, intelligent driving navigation and obstacle avoidance, and 3D sensing in consumer electronics. Lastly, the paper analyzes the future development trends and forecasts the potential challenges of single-photon LiDAR technology in detectors, algorithms, systems, and application domains.
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Overview: 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.
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图 7 SPL100数据处理前后点云去噪效果图
Figure 7. Point cloud before and after data processing for the SPL100
图 8 啁啾调制单光子激光雷达的成像算法效果图[61]。(a) 目标场景“Art”的精确深度图；(b) 不同条件下不同算法成像效果；(c)不同方法的光子利用率
Figure 8. 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
图 11 201.5 km远距离单光子探测成像系统及成像结果[11]。(a) 201.5 km 远距离单光子探测成像系统；(b) 目标图片；(c) Lindell所提算法效果；(d)三维重构轮廓
Figure 11. 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
图 17 (a) ZVISION EZ6的性能参数及点云效果；(b) iPhone12 Pro三维成像效果图
Figure 17. (a) Performance metrics and imaging results of ZVISION EZ6; (b) The result of 3D imaging by iPhone 12 Pro
表 1 Si SPAD探测器的最新进展和重要参数
Table 1. Recent progress and important parameters of Si SPAD detectors
Reference Technology Year Size/μm Timing jitter/ps Dead time/ns AP/% DCR/cps Peak PDE [38] 65 nm standard CMOS 2018 20 7.8 100 <10 2800 8%@470 nm [39] 65 nm standard CMOS 2021 10 139 3.5 - 233 23.8@420 nm [40] 130 nm CIS 2019 23.78 127 - - 50 25%@465 nm [36] 180 nm CIS 2020 9.4 - - - 0.4 26.7%@520 nm [41] 180 nm CIS 2021 50 16 50 <3 0.23 55%@480 nm [42] 110 nm CIS 2023 10 68 - 0.15 12.6 73%@440 nm [43] 160 nm BCD 2021 10/20/30 75 0.9/1.9 0.14/0.09 0.19 64%@490 nm [44] 55 nm BCD 2021 8.8 52 0.97 0.97 0.1 62%@530 nm [45] 55 nm BCD 2023 14.4 55 2500 0 38.2 89.4%@450 nm 
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表 2 InGaAs/InP SPAD探测器的最新进展和重要参数
Table 2. Recent progress and important parameters of InGaAs/InP SPAD detectors
Reference Year Size/μm Timing Jitter
/psDead
time/nsAP/% DCR/cps Peak PDE [52] 2018 <100 - 2 <2 - 10%@1060 nm [50] 2020 - - 88 5.5 3k@253 K 40%@1550 nm [53] 2021 - 70 - 4.5 20k@225 K 50%@1550 nm [54] 2022 20 - - - 43.8k@247 K 55.4%@1550 nm [55] 2022 25 - - - 9.09k@223 K 25.72%@1550 nm [49] 2022 10 159 - - 1k@225 K 33%@1064 nm [56] 2023 - 44 20 1.4 - 21%@1550 nm
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表 3 SPAD激光雷达在远距离探测的最新进展和重要参数
Table 3. Recent progress and important parameters of SPAD LiDAR in long-range detection
Reference Year System Distance
/kmWavelength/nm Power/mW Array Mode FOV/μrad PDE/% Aperture
/mm[74] 2013 Pulse accumulation 4.5 1550 <0.6 64 × 64 flash 3800 26 - [75] 2014 Random coding 1.77 1550 63800
(peak)- - - - 50 [69] 2017 Pulse accumulation 10.5 1550 10 - scan 28 ~30 210 [76] 2017 Pulse accumulation 2.5 532 3 100*1 scan 24750 ~36.8 95 [70] 2018 Pulse accumulation 21 1550 0.5 - scan 80 ~3.58 130 [71] 2020 Pulse accumulation 8.2 1550 120 128 × 128 scan 22.3 35 279 [73] 2020 Pulse accumulation 45 1550 120 1*1 scan 22.3 15 - [11] 2021 Pulse accumulation 201.5 1550 600 1*1 scan 11.2 19.3 280 [77] 2023 Pulse accumulation 13.8 1550 300 - scan - - -
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表 4 部分公司单光子激光雷达产品
Table 4. Single-photon LiDAR products of partial companies
Company Year Product FOV Distance/m Power/W Frame Ouster 2020 ES2 26°(H) × 13°(V) 200 12~18 10~30 Ouster 2020 OS2 360°(H) × 22.5°(V) 200 18~24 20 南京芯视界 2020 VI4330 73°(H) × 58°(V) 15 - 30 IBEO 2021 Ibeonext 11.2°(H) × 5.6°(V) 140 - - Sense Photonics 2021 MultiRangeTM - 200 - - 亮道智能 2022 LDSatellite 120°(H) × 75°(V) 30 ＜10 10~25 速腾聚创 2022 RS-LiDAR-E1 120°(H) × 90°(V) 30 - 10~30 禾赛科技 2023 ET25 120°(H) × 25°(V) 250 12 10/20 SolidVue 2023 ES - 200 - - 一径科技 2023 ZVISION EZ6 120°(H) × 20°(V) 180 <15 - 华为 2023 - - 250 - 20 灵明光子 2023 ADS6311 ToF 120°(H) × 90°(V) 30 3 20
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