Abstract
Time-of-Flight (TOF) based Light Detection and Ranging (LiDAR) is a widespread technique for distance measurements in both single-spot depth ranging and 3D mapping. Single Photon Avalanche Diode (SPAD) detectors provide single-photon sensitivity and allow in-pixel integration of a Time-to-Digital Converter (TDC) to measure the TOF of single-photons. From the repetitive acquisition of photons returning from multiple laser shots, it is possible to accumulate a TOF histogram, so as to identify the laser pulse return from unwelcome ambient light and compute the desired distance information. In order to properly predict the TOF histogram distribution and design each component of the LiDAR system, from SPAD to TDC and histogram processing, we present a detailed statistical modelling of the acquisition chain and we show the perfect matching with Monte Carlo simulations in very different operating conditions and very high background levels. We take into consideration SPAD non-idealities such as hold-off time, afterpulsing, and crosstalk, and we show the heavy pile-up distortion in case of high background. Moreover, we also model non-idealities of timing electronics chain, namely, TDC dead-time, limited number of storage cells for TOF data, and TDC sharing. Eventually, we show how the exploit the modelling to reversely extract the original LiDAR return signal from the distorted measured TOF data in different operating conditions.
Highlights
Light Detection and Ranging (LiDAR) is an optical technique widely used to measure the distance of a target and to acquire 3D depth-resolved maps of a scene, and is employed in several fields of science and everyday life, such as automotive applications [1], gesture recognition [2], 3D scanners for virtual prototyping [3], and security surveillance.In Time-of-Flight (TOF) LIDAR, the target is illuminated with light and a camera collects backscattered photons to evaluate the distance of the target; depending on the light modulation, this can be performed in different ways [4,5]
In order to provide a valuable tool for the sizing of these components and the simulation of the expected acquisition waveforms of signal and background photons, we have developed a detailed statistical modelling for Single Photon Avalanche Diode (SPAD)-based LiDAR systems
A time stamp is possible if an event triggers the detector, in order to reduce the impact of the timing electronics dead-time, by rou to-Digital Converter (TDC) and the number of TDC is not saturated (TDCSAT)
Summary
Light Detection and Ranging (LiDAR) is an optical technique widely used to measure the distance of a target and to acquire 3D depth-resolved maps of a scene, and is employed in several fields of science and everyday life, such as automotive applications [1], gesture recognition [2], 3D scanners for virtual prototyping [3], and security surveillance. Diode (SPAD) detectors and SPAD arrays can be employed as TOF imagers, thanks to their single-photon sensitivity and ability to integrate one Time-to-Digital Converter (TDC) in each pixel, allowing to reconstruct high frame rate 3D images [7] Their gating capability can be exploited to image defined regions of interest in the distance plane, suppress direct leakage between illumination laser beam and sensor (e.g., when both are physically placed in the same enclosure), or even to suppress specific reflections from objects inside the scene, allowing for applications such as around-the-corner imaging [8], where the content of a scene hidden from direct line of sight can be reconstructed exploiting multiple reflections of a light beam. Time-Correlated Single Photon Counting setups and multi-photon acquisitions
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
