256 $\times$  TDC Array With Cyclic Interpolators Based on Calibration-Free $2{\times}$  Time Amplifier

Keränen, Pekka; Kostamovaara, J.

doi:10.1109/tcsi.2018.2868242

Cited by 20 publications

(10 citation statements)

References 16 publications

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“…The interpolators utilize delay line based PVT tolerant pulse width doublers to construct a cyclic data converter. A detailed description of the cyclic interpolators and the performance of the whole TDC array is provided in [26]. The performance of the TDCs has been measured to provide a single-shot precision of about 70ps, while the DNL and INL for the TDCs are +0.3/ − 0.2LSBs and +1.3/ − 1LSBs, respectively.…”

Section: Receiver Architecture and Circuit Detailsmentioning

confidence: 99%

$256\times8$ SPAD Array With 256 Column TDCs for a Line Profiling Laser Radar

Keränen

Kostamovaara

2019

IEEE Trans. Circuits Syst. I

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A receiver circuit for pulsed time-of-flight line profiling laser radar has been designed in 0.35µm CMOS technology. The receiver consists of a line detector array with 256×8 SPADs with a pitch of 41.6µm. The diameter of the SPAD's active area is 25.6µm, which gives a fill factor of 0.35. Each column has 8 SPADs and a TDC with a range and resolution of 640 ns and 20 ps, respectively. The TDCs are based on the Nutt interpolation method where cyclic converters are utilized as fine converters. A compact demonstrator system has been built with a horizontal FOV of about 37 • , which gives a column-wise angular resolution of about 0.15 •. This solid-state system uses a pulsed laser diode with cylindrical transmitter optics to illuminate the full FOV of the receiver with a single laser pulse. The system can measure distances up to 30 m @ 28 fps with an accuracy and precision of few millimeters in typical indoor lighting conditions. Outdoors, in direct sunlight conditions, the measurement range is decreased to 5 m. Outdoor range, however, can be increased if frame rate is lowered and more laser shots are accumulated per frame. Index Terms-Time-to-digital converter (TDC), single photon avalanche diode (SPAD), time-of-flight (ToF), light detection and ranging (LiDAR). I. INTRODUCTION P ULSED time-of-flight (TOF) laser radar operates on the principle of sending a high power (>10W) and short (<5ns) laser pulse towards the target, and then measuring the time-of-flight by measuring the time difference between the transmitted pulse and the reflected echo pulse [1]-[4]. Since the velocity of light is relatively constant, the distance to the target can be calculated based on the measured transit time. These techniques have important advantages compared to other optical time-of-light methods, e.g. to the measurement of the phase difference between the transmitted continuous-wave (CW) optical signal and the reflected echo. For a pulsed TOF system, the non-ambiguous measurement range is limited basically by the pulsing rate of the transmitter and can thus be very long (i.e. 100m with 1MHz) whereas in the CW phase comparison techniques there is a trade-of between the non-ambiguous

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Section: Receiver Architecture and Circuit Detailsmentioning

confidence: 99%

$256\times8$ SPAD Array With 256 Column TDCs for a Line Profiling Laser Radar

Keränen

Kostamovaara

2019

IEEE Trans. Circuits Syst. I

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“…The experimental single-photon solid-state lidar that we use here is presented in and has been assembled by the authors of (Keränen, Kostamovaara, 2019), see Figure 1 (a). It is an advanced design of the one in (Keränen, Kostamovaara, 2018). The lidar has a range of up to 96 m (640 ns) and an opening angle of about 37 degrees.…”

Section: Related Workmentioning

confidence: 99%

“…The scanner is essentially a line scanner. However, in contrast to (Keränen, Kostamovaara, 2018), each channel has 8 receivers, i.e. single photon avalanche diodes (SPADs), stacked on top of one another (Keränen, Kostamovaara, 2019).…”

Section: Related Workmentioning

confidence: 99%

“…Hence, we model the noise distribution directly from the sample, such as the one in Figure 2 (a), and pre-process the signal as in Figure 2 (b) but with a smaller sample size as explained in the following. These steps are done as in the baseline method used in (Keränen, Kostamovaara, 2019, Keränen, Kostamovaara, 2018.…”

Section: Long Range Detectionmentioning

confidence: 99%

“…Therefore, in this paper, we focus on examining the data obtained from a 256 channel single-photon solid-state lidar (Keränen, Kostamovaara, 2018). Our purpose is to adapt and utilize the Channel index [1,256] Figure 1.…”

Section: Introductionmentioning

confidence: 99%

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Single Photon Lidar in Mobile Laser Scanning: The Sampling Rate Problem and Initial Solutions via Spatial Correlations

Lehtola

Hyyti

Keränen

et al. 2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Single photon lidars (in solid state form) offer several benefits over pulsed lidars, such as independence of micro-mechanical moving parts or rotating joints, lower power consumption, faster acquisition rate, and reduced size. When mass produced, they will be cheaper and smaller and thus very attractive for mobile laser scanning applications. However, as these lidars operate by receiving single photons, they are very susceptible to background illumination such as sunlight. In other words, the observations contain a significant amount of noise, or to be specific, outliers. This causes trouble for measurements done in motion, as the sampling rate (i.e. the measurement frequency) should be low and high at the same time. It should be low enough so that target detection is robust, meaning that the targets can be distinguished from the single-photon avalanche diode (SPAD) triggings caused by the background photons. On the other hand, the sampling rate should be high enough to allow for measurements to be done from motion. Quick sampling reduces the probability that a sample gathered during motion would contain data from more than a single target at a specific range. Here, we study the exploitation of spatial correlations that exist between the observations as a mean to overcome this sampling rate paradox. We propose computational methods for short and long range. Our results indicate that the spatial correlations do indeed allow for faster and more robust sampling of measurements, which makes single photon lidars more attractive in (daylight) mobile laser scanning.

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Trench visualisation from a semiautonomous excavator with a base grid map using a TOF 2D profilometer

Niskanen

Immonen

Makkonen

et al. 2023

J Vis

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Real-time, three-dimensional (3D) visualisation technology can be used at construction sites to improve the quality of work. A 3D view of the landscape under work can be compared to a target 3D model of the landscape to conveniently show needed excavation tasks to a human excavator operator or to show the progress of an autonomous excavator. The purpose of this study was to demonstrate surface visualisation from measurements taken with a pulsed time-of-flight (TOF) 2D profilometer on-board a semiautonomous excavator. The semiautomatic excavator was implemented by recording the feedback script parameters from the work performed on the excavator by a human driver. 3D visualisation maps based on the triangle mesh technique were generated from the 3D point cloud using measurements of the trenches dug by a human and an autonomous excavator. The accuracy of the 3D maps was evaluated by comparing them to a high-resolution commercial 3D scanner. An analysis of the results shows that the 2D profilometer attached to the excavator can achieve almost the same 3D results as a high-quality on-site static commercial 3D scanner, whilst more easily providing an unobstructed view of the trench during operation (a 3D scanner placed next to a deep trench might not have a full view of the trench). The main technical advantages of our 2D profilometer are its compact size, measurement speed, lack of moving parts, robustness, low-cost technology that enables visualisations from a unique viewpoint on the boom of the excavator, and readiness for real-time control of the excavator’s system. This research is expected to encourage the efficiency of the digging process in the future, as well as to provide a remarkable view of trench work using an excavator as a moving platform to facilitate data visualisation. Graphical abstract

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256 $\times$ TDC Array With Cyclic Interpolators Based on Calibration-Free $2{\times}$ Time Amplifier

Cited by 20 publications

References 16 publications

$256\times8$ SPAD Array With 256 Column TDCs for a Line Profiling Laser Radar

$256\times8$ SPAD Array With 256 Column TDCs for a Line Profiling Laser Radar

Single Photon Lidar in Mobile Laser Scanning: The Sampling Rate Problem and Initial Solutions via Spatial Correlations

Trench visualisation from a semiautonomous excavator with a base grid map using a TOF 2D profilometer

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