A review of SPAD array chip design for direct time-of-flight LiDAR
Source abstract
Abstract
As the requirements of LiDAR for data processing volume, ranging accuracy, and anti-interference capability continue to rise, significant transformations have occurred in recent years in the system architecture, data flow design, and algorithm modules of LiDAR receiver chips. This paper reviews the current design status of direct Time-of-Flight (dToF) ranging sensor chips, focusing on three key aspects for systematic summarization: first, innovations in ranging methods, covering two novel technical schemes, namely histogram-free and variable histogram resolution; second, anti-interference and accuracy optimization, including the chip's suppression of ambient light, mitigation of inter-LiDAR interference, and calibration methods for ranging accuracy; third, comprehensive design optimization of chip Power, Performance, and Area (PPA). Finally, several targeted improvement suggestions are put forward to address existing design bottlenecks, providing references for the subsequent research and development of ToF ranging sensor chips.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Optical Sensing Technologies · Indoor and Outdoor Localization Technologies · Radar Systems and Signal Processing
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (89)
Show source-provided references
1. Fung TC, Wang C, Wang H, Albason ACB, Siddique RH, Wang YM. An efficient direct time-of-flight (dtof) lidar system based on high resolution spad array
2. Ronchini Ximenes A, Padmanabhan P, Charbon E. Mutually coupled time-to-digital converters (tdcs) for direct time-of-flight (dtof) image sensors. Sensors. 2018;18(10):3413.10.3390/s18103413 ↗
3. Kostamovaara J, Huikari J, Hallman L, Nissinen I, Nissinen J, Rapakko H, et al. On laser ranging based on high-speed/energy laser diode pulses and single-photon detection techniques. IEEE Photon J. 2015;7(2):1–15.10.1109/JPHOT.2015.2402129 ↗
4. Gyongy I, Dutton NA, Henderson RK. Direct time-of-flight single-photon imaging. IEEE Trans Electron Devices. 2021;69(6):2794–805.10.1109/TED.2021.3131430 ↗
5. Incoronato A, Locatelli M, Zappa F. Statistical modelling of spads for time-of-flight lidar. Sensors. 2021;21(13):4481.10.3390/s21134481 ↗
6. Zhao J, Milanese T, Gramuglia F, Keshavarzian P, Tan SS, Tng M, Lim L, Dhulla V, Quek E, Lee M-J. On analog silicon photomultipliers in standard 55-nm bcd technology for lidar applications. IEEE J Sel Top in Quantum Electron 28(5: Lidars and Photonic Radars), 2022;1–10.10.1109/JSTQE.2022.3161089 ↗
7. Liu M, Liu B, Hu J, Li D, Ma J, Chu Z, et al. A 16-channel analog cmos sipm with on-chip front-end for d-tof lidar. IEEE Trans Circuits Syst I Regul Pap. 2022;69(6):2376–86.10.1109/TCSI.2022.3160265 ↗
8. Gnecchi S, Jackson C. A 1$$\times $$ 16 sipm array for automotive 3d imaging lidar systems. In: Proceedings of the 2017 International Image Sensor Workshop (IISW), Hiroshima, Japan, 2017;133–136.
9. Al Abbas T, Dutton NA, Almer O, Finlayson N, Della Rocca FM, Henderson R. A cmos spad sensor with a multi-event folded flash time-to-digital converter for ultra-fast optical transient capture. IEEE Sens J. 2018;18(8):3163–73.10.1109/JSEN.2018.2803087 ↗
10. Arvani F, Carusone TC, Rogers ES. Tdc sharing in spad-based direct time-of-flight 3d imaging applications. In: 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019;1–5. IEEE10.1109/ISCAS.2019.8702586 ↗
11. Arvani F, Carusone TC. A reconfigurable 5-channel ring-oscillator-based tdc for direct time-of-flight 3d imaging. IEEE Trans Circuits Syst II Express Briefs. 2022;69(5):2408–12.
12. Aull BF, Collins M, Donlan K, Ciampi J, Punjiya M, McIntosh KA, Ryu K, Woods D. Mitigation of optical crosstalk in geiger-mode avalanche photodiode arrays for lidar. In: Advanced Photon Counting Techniques XVI, vol. 12089, 2022; 98–104. SPIE10.1117/12.2618169 ↗
13. BenMoussa A, Giordanengo B, Gissot S, Meynants G, Wang X, Wolfs B, Bogaerts J, Schühle U, Berger G, Gottwald A. 64$$\times $$ 64-pixel digital silicon photomultiplier direct tof sensor with 100mphotons/s/pixel background rejection and imaging/altimeter mode with 0.14 precision up to 6km for spacecraft navigation and landing. In: Proceedings of the 2016 IEEE International Solid-State Circuits Conference (ISSCC), 2016; 118–120.10.1109/ISSCC.2016.7417935 ↗
14. Seo H, Yoon H, Kim D, Kim J, Kim S-J, Chun J-H, et al. Direct tof scanning lidar sensor with two-step multievent histogramming tdc and embedded interference filter. IEEE J Solid-State Circuits. 2021;56(4):1022–35.10.1109/JSSC.2020.3048074 ↗
15. Piron F, Morrison D, Yuce MR, Redouté J-M. A review of single-photon avalanche diode time-of-flight imaging sensor arrays. IEEE Sens J. 2021;21(11):12654–66. https://doi.org/10.1109/JSEN.2020.3039362.10.1109/JSEN.2020.3039362 ↗
16. Bruschini CE, Homulle HAR, Antolović IM, Burri S, Charbon E. Single-photon avalanche diode imagers in biophotonics: review and outlook. Light, Science & Applications 2019;810.1038/s41377-019-0191-5 ↗
17. Chen G, Wiede C, Kokozinski R. Data processing approaches on spad-based d-tof lidar systems: a review. IEEE Sens J. 2021;21(5):5656–67. https://doi.org/10.1109/JSEN.2020.3038487.10.1109/JSEN.2020.3038487 ↗
18. Villa F, Severini F, Madonini F, Zappa F. Spads and sipms arrays for long-range high-speed light detection and ranging (lidar). Sensors. 2021;21(11):3839. https://doi.org/10.3390/s21113839.10.3390/s21113839 ↗
19. Yoshioka K. A tutorial and review of automobile direct tof lidar socs: Evolution of next-generation lidars. IEICE Trans Electron. 2022;105:534–43.10.1587/transele.2021CTI0002 ↗
20. Li N, Ho CP, Xue JXJ, Lim LW, Chen G, Fu YH, et al. A progress review on solid-state lidar and nanophotonics-based lidar sensors. Laser & Photonics Rev. 2022;16(11):2100511.10.1002/lpor.202100511 ↗
21. Hashemi H. A review of silicon photonics lidar. 2022 IEEE Custom Integrated Circuits Conference (CICC), 2022;1–8.10.1109/CICC53496.2022.9772845 ↗
22. Padmanabhan P, Zhang C, Cazzaniga M, Efe B, Ximenes AR, Lee M-J, Charbon E. 7.4 a 256$$\times $$ 128 3d-stacked (45nm) spad flash lidar with 7-level coincidence detection and progressive gating for 100m range and 10klux background light. In: 2021 IEEE International Solid-State Circuits Conference (ISSCC), 2021;64:11–113. IEEE.10.1109/ISSCC42613.2021.9366010 ↗
23. Carimatto A, Mandai S, Venialgo E, Gong T, Borghi G, Schaart DR, Charbon E. 11.4 a 67,392-spad pvtb-compensated multi-channel digital sipm with 432 column-parallel 48ps 17b tdcs for endoscopic time-of-flight pet. In: 2015 IEEE International Solid-State Circuits Conference-(ISSCC) Digest of Technical Papers, 2015;1–3. IEEE10.1109/ISSCC.2015.7062996 ↗
24. Hutchings SW, Johnston N, Gyongy I, Al Abbas T, Dutton NA, Tyler M, et al. A reconfigurable 3-d-stacked spad imager with in-pixel histogramming for flash lidar or high-speed time-of-flight imaging. IEEE J Solid-State Circuits. 2019;54(11):2947–56.10.1109/JSSC.2019.2939083 ↗
25. Gyongy I, Erdogan AT, Dutton NA, Martín GM, Gorman A, Mai H, Della Rocca FM, Henderson RK. A direct time-of-flight image sensor with in-pixel surface detection and dynamic vision. IEEE Journal of Selected Topics in Quantum Electronics 2023.10.1109/JSTQE.2023.3238520 ↗
26. Taneski F, Al Abbas T, Henderson RK. Laser power efficiency of partial histogram direct time-of-flight lidar sensors. J Lightwave Technol. 2022;40(17):5884–93.10.1109/JLT.2022.3187293 ↗
27. Chen G, Wiede C, Kokozinski R. Data processing approaches on spad-based d-tof lidar systems: a review. IEEE Sens J. 2020;21(5):5656–67.10.1109/JSEN.2020.3038487 ↗
28. Faizan S, Jainwal K, Bisen M, Khanna N. A spad based multi-mode compressive lidar pixel for depth ranging by direct tof measurement
29. Seo H, Cho G, Kim S-J, Chun J-H, Choi J. Multievent histogramming tdc with pre-post weighted histogramming filter for cmos lidar sensors. IEEE Sens J. 2022;22(23):22785–98.10.1109/JSEN.2022.3217303 ↗
30. Zhang C, Lindner S, Antolović IM, Mata Pavia J, Wolf M, Charbon E. A 30-frames/s, $$252\times 144$$ spad flash lidar with 1728 dual-clock 48.8-ps tdcs, and pixel-wise integrated histogramming. IEEE J Solid-State Circuits. 2019;54(4):1137–51. https://doi.org/10.1109/JSSC.2018.2883720.10.1109/JSSC.2018.2883720 ↗
31. Sharma AK, Laflaquière A, Agranov GA, Rosenblum G, Mandai S. SPAD array with gated histogram construction. Google Patents. US Patent 2020;10,620,300.
32. Milanese T, Zhao J, Hearn B, Charbon E. Histogram-less direct time-of-flight imaging based on a machine learning processor on fpga
33. White M, Zhang T, Dave A, Ghajari S, Molnar A, Veeraraghavan A. Fad-spads: a new paradigm for designing single-photon detecting arrays 2023.
34. Ingle A, Maier D. Count-free single-photon 3d imaging with race logic. IEEE Transactions on Pattern Analysis and Machine Intelligence 2023.
35. Madhavan A, Sherwood T, Strukov D. Race logic: a hardware acceleration for dynamic programming algorithms. ACM SIGARCH Comput Arch News. 2014;42(3):517–28.10.1145/2678373.2665747 ↗
36. Süss A, Rochus V, Rosmeulen M, Rottenberg X. Benchmarking time-of-flight based depth measurement techniques. In: Smart Photonic and Optoelectronic Integrated Circuits XVIII, 2016;9751:99–217. SPIE10.1117/12.2212478 ↗
37. Pasquinelli K, Lussana R, Tisa S, Villa F, Zappa F. Single-photon detectors modeling and selection criteria for high-background lidar. IEEE Sens J. 2020;20(13):7021–32.10.1109/JSEN.2020.2977775 ↗
38. Gallivanoni A, Rech I, Ghioni M. Progress in quenching circuits for single photon avalanche diodes. IEEE Trans Nucl Sci. 2010;57(6):3815–26.
39. Acconcia G, Cominelli A, Ghioni M, Rech I. Fast fully-integrated front-end circuit to overcome pile-up limits in time-correlated single photon counting with single photon avalanche diodes. Opt Express. 2018;26(12):15398–410.10.1364/OE.26.015398 ↗
40. Hayat MM, Torres SN, Pedrotti LM. Theory of photon coincidence statistics in photon-correlated beams. Optics commn. 1999;169(1–6):275–87.10.1016/S0030-4018(99)00384-3 ↗
41. Niclass C, Soga M, Matsubara H, Ogawa M, Kagami M. A 0.18-$$\mu $$m cmos soc for a 100-m-range 10-frame/s 200$$\times $$96-pixel time-of-flight depth sensor. IEEE J Solid-State Circuits. 2013;49(1):315–30.10.1109/JSSC.2013.2284352 ↗
42. Padmanabhan P, Zhang C, Charbon E. Modeling and analysis of a direct time-of-flight sensor architecture for lidar applications. Sensors. 2019;19(24):5464.10.3390/s19245464 ↗
43. Zhou H, Chen Q, Sun M, Xu J, Nie K. Ambient light rejection method for multiphoton coincidence detection in single-photon avalanche diode-based dtof sensors. Appl Opt. 2023;62(7):1807–14.10.1364/AO.482050 ↗
44. Incoronato A, Cusini I, Pasquinelli K, Zappa F. Single-shot pulsed-lidar spad sensor with on-chip peak detection for background rejection. IEEE J Sel Top Quantum Electron. 2022;28(5):1–10.
45. Sesta V, Pasquinelli K, Federico R, Zappa F, Villa F. Range-finding spad array with smart laser-spot tracking and tdc sharing for background suppression. IEEE Open J Solid-State Circ Soc. 2021;2:26–37.10.1109/OJSSCS.2021.3116920 ↗
46. Ximenes AR, Padmanabhan P, Lee M-J, Yamashita Y, Yaung D-N, Charbon E. A modular, direct time-of-flight depth sensor in 45/65-nm 3-d-stacked cmos technology. IEEE J Solid-State Circ. 2019;54(11):3203–14.10.1109/JSSC.2019.2938412 ↗
47. Shalaby HM. Cochannel interference reduction in optical ppm-cdma systems. IEEE Trans Commun. 1998;46(6):799–805.10.1109/26.681419 ↗
48. Chung FR, Salehi JA, Wei VK. Optical orthogonal codes: design, analysis and applications. IEEE Trans Inf Theory. 1989;35(3):595–604.10.1109/18.30982 ↗
49. Fersch T, Weigel R, Koelpin A. A cdma modulation technique for automotive time-of-flight lidar systems. IEEE Sens J. 2017;17(11):3507–16.10.1109/JSEN.2017.2688126 ↗
50. Carrara L, Fiergolski A. An optical interference suppression scheme for tcspc flash lidar imagers. Appl Sci. 2019;9(11):2206.10.3390/app9112206 ↗
51. Sesta V, Incoronato A, Madonini F, Villa F. Time-to-digital converters and histogram builders in spad arrays for pulsed-lidar. Measurement. 2023;212:112705.10.1016/j.measurement.2023.112705 ↗
52. Alvarez JL. Poisson-based detection limit and signal confidence intervals for few total counts. Health Phys. 2007;93(2):120–6.10.1097/01.HP.0000261331.73389.bd ↗
53. Davis C, King T. Correction methods for photon pile-up in lifetime determination by single-photon counting. J Phys A: Gen Phys. 1970;3(1):101.10.1088/0305-4470/3/1/013 ↗
54. Coates P. The correction for photonpile-up’in the measurement of radiative lifetimes. J Phys E: Sci Instrum. 1968;1(8):878.10.1088/0022-3735/1/8/437 ↗
55. Pediredla AK, Sankaranarayanan AC, Buttafava M, Tosi A, Veeraraghavan A. Signal processing based pile-up compensation for gated single-photon avalanche diodes. 2018. arXiv:1806.07437.
56. Yanfang L, Jie C, Yong X, Yizun W, Shaoqing X. The invention discloses a laser radar calibration method and a laser radar 2022.
57. Lang N, Kalischek N, Armston J, Schindler K, Dubayah R, Wegner JD. Global canopy height regression and uncertainty estimation from gedi lidar waveforms with deep ensembles. Remote Sens Environ. 2022;268:112760.10.1016/j.rse.2021.112760 ↗
58. Burri S. Challenges and solutions to next-generation single-photon imagers. EPFL: Technical report; 2016.
59. Gundacker S, Heering A. The silicon photomultiplier: fundamentals and applications of a modern solid-state photon detector. Phys Med & Bio. 2020;65(17):17–01.10.1088/1361-6560/ab7b2d ↗
60. Qianyuan C, Xiang L, Zhenping Y, et al. Afterpulse correction of silicon single-photon detector for 1064-nm aerosol-lidar. Opt Express. 2024;32(27):47959–69.10.1364/OE.542442 ↗
61. Chao Y, et al. Fully integrated free-running InGaAs/InP single-photon detector for accurate lidar applications. Opt Express. 2017;25(13):14611–20.10.1364/OE.25.014611 ↗
62. Abdelghafar A, Morimoto K, Sekine H, Tsuchiya H, Shinohara M, Ota Y, Iwata J, Matsuno Y, Sakurai K, Ichikawa T. Light-emission crosstalk model and dynamic correction algorithm for large-scale spad image sensors
63. Ogi J, Sano F, Nakata T, Kubo Y, Onishi W, Koswaththaghe C, Mochizuki T, Tashiro Y, Hizu K, Takatsuka T, et al. A 3.06 $$\mu $$m spad pixel with embedded metal contact and power grid on deep trench pixel isolation for high-resolution photon-counting
64. Tsai S-Y, Chang Y-C, Sang T-H. Spad lidars: Modeling and algorithms. In: 2018 14th IEEE International Conference on Solid-State and Integrated Circuit Technology (ICSICT), 2018;1–4. IEEE10.1109/ICSICT.2018.8565812 ↗
65. Phillips TG, Guenther N, McAree PR. When the dust settles: the four behaviors of lidar in the presence of fine airborne particulates. J field robot. 2017;34(5):985–1009.10.1002/rob.21701 ↗
66. Olsen MJ, Parrish C, Che E, Jung J, Greenwood J, et al. Lidar for maintenance of pavement reflective markings and retroreflective signs. Technical report: Oregon. Dept. of Transportation; 2018.
67. Che E, Olsen MJ, Parrish CE, Jung J. Pavement marking retroreflectivity estimation and evaluation using mobile lidar data. Photogrammetric Eng Remote Sens. 2019;85(8):573–83.10.14358/PERS.85.8.573 ↗
68. Bennett H, Porteus J. Relation between surface roughness and specular reflectance at normal incidence. JOSA. 1961;51(2):123–9.10.1364/JOSA.51.000123 ↗
69. Fest E. Stray Light Analysis and Control, 2013.10.1117/3.1000980 ↗
70. Gärtner A, Sabbagh A, Schulz U, Rickelt F, Bingel A, Wolleb S, et al. Combined antifogging and antireflective double nanostructured coatings for lidar applications. Appl Opt. 2023;62(7):112–6.10.1364/AO.476974 ↗
71. Jiang H, Niu X. Stray light analysis and suppression of the visible to terahertz integrated cloud detection optical system. Sensors. 2023;23(8):4115.10.3390/s23084115 ↗
72. Lee S, Lee D, Choi P, Park D. Accuracy-power controllable lidar sensor system with 3d object recognition for autonomous vehicle. Sensors. 2020;20(19):5706.10.3390/s20195706 ↗
73. Chossat J. Image sensors in 3d stacking technology retrospective and perspectives from a digital architect point of view
74. Hornung A, Wurm KM, Bennewitz M, Stachniss C, Burgard W. Octomap: an efficient probabilistic 3d mapping framework based on octrees. Auton Robot. 2013;34:189–206.10.1007/s10514-012-9321-0 ↗
75. Golla T, Klein R. Real-time point cloud compression. In: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015;5087–5092. IEEE10.1109/IROS.2015.7354093 ↗
76. Kuang S-R, Jou J-M, Chen Y-L. The design of an adaptive on-line binary arithmetic-coding chip. IEEE Transn Circ Syst I Fundamental Theory Appl. 1998;45(7):693–706.
77. Leavline EJ, Singh D. Hardware implementation of lzma data compression algorithm. Intl J Appl Inform Syst (IJAIS). 2013;5(4):51–6.
78. Rice R, Plaunt J. Adaptive variable-length coding for efficient compression of spacecraft television data. IEEE Trans Commun Technol. 1971;19(6):889–97.10.1109/TCOM.1971.1090789 ↗
79. Halimi A, Ciuciu P, Mccarthy A, Mclaughlin S, Buller GS. Fast adaptive scene sampling for single-photon 3d lidar images. In: 2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2019;196–200. IEEE10.1109/CAMSAP45676.2019.9022519 ↗
80. Sheehan MP, Tachella J, Davies ME. A sketching framework for reduced data transfer in photon counting lidar. IEEE Trans Comput Imaging. 2021;7:989–1004.10.1109/TCI.2021.3113495 ↗
81. Veerappan C, Richardson J, Walker R, Li D-U, Fishburn MW, Maruyama Y, Stoppa D, Borghetti F, Gersbach M, Henderson RK. A 160$$\times $$ 128 single-photon image sensor with on-pixel 55ps 10b time-to-digital converter. In: 2011 IEEE International Solid-State Circuits Conference, 2011;312–314. IEEE10.1109/ISSCC.2011.5746333 ↗
82. Park D, Youn JM, Cho J, et al. A low-power microcontroller with accuracy-controlled event-driven signal processing unit for rare-event activity-sensing iot devices. J Sens. 2015;2015(1):809201.10.1155/2023/9207750 ↗
83. Braga LH, Gasparini L, Grant L, Henderson RK, Massari N, Perenzoni M, et al. A fully digital 8$$\times $$16 sipm array for pet applications with per-pixel tdcs and real-time energy output. IEEE J Solid-State Circuits. 2013;49(1):301–14.10.1109/JSSC.2013.2284351 ↗
84. Tontini A, Gasparini L, Passerone R. A spad-based linear sensor with in-pixel temporal pattern detection for interference and background rejection with smart readout scheme
85. Popa C. Low-power low-voltage cmos analog signal processing circuits using a functional core. In: 2016 IEEE International Conference on Electronics, Circuits and Systems (ICECS), 2016;680–683. IEEE10.1109/ICECS.2016.7841293 ↗
86. Malik M, Homayoun H. Big data on low power cores: Are low power embedded processors a good fit for the big data workloads? In: 2015 33rd IEEE International Conference on Computer Design (ICCD), 2015; 379–382. IEEE10.1109/ICCD.2015.7357128 ↗
87. Lorenzon AF, Cera MC, Beck ACS. On the influence of static power consumption in multicore embedded systems. In: 2015 IEEE International Symposium on Circuits and Systems (ISCAS), 2015;1374–1377. IEEE10.1109/ISCAS.2015.7168898 ↗
88. Lee Y, Park M. Power consumption and accuracy in detecting pedestrian images on neuromorphic hardware accelerated embedded systems. In: 2019 Tenth International Green and Sustainable Computing Conference (IGSC), 2019;1–4. IEEE10.1109/IGSC48788.2019.8957210 ↗
89. Li K. Optimal task execution speed setting and lower bound for delay and energy minimization. J Parallel Distributed Comput. 2019;123:13–25.10.1016/j.jpdc.2018.09.003 ↗