Long range LiDAR characterisation for obstacle detection for use by the visually impaired and blind

Obstacle detection and avoidance is a huge area of interest for autonomous vehicles and, as such, has become an important research topic. Detecting and identifying obstacles enables navigation through an ever changing environment. This work looks at the technology used in self-driving vehicles and examines whether the same technology could be used to aid in navigation for visually impaired and blind (VIB) people. For autonomous vehicles, obstacle detection relies on different sensor modalities to provide information on the vehicles surroundings. A combination of the same sensors placed on a white cane could be used to perform free-space assessment over the whole height of the user and provide additional environmental information not available from the cane alone. This provides its own challenges and advantages. The speeds are much slower when dealing with pedestrians and scanning can be achieved by the movement of the cane. However, the weight and size must be significantly reduced. The full system will be integrated into a smart cane and will consist of four main sensors as well as range sensors. The aim of this work is to report on the characterisation of a long range LiDAR (up to 10m) that will be integrated into a smart white cane developed as part of the INSPEX H2020 project

Digital Silicon Photomultipliers with OR/XOR Pulse Combining Techniques

A recently proposed XOR-based digital silicon photomultiplier (dSiPM) is compared against the OR-based counterpart. We show experimental data from a set of single-photon avalanche diode (SPAD) pixel arrays in 130-nm CMOS process with selectable OR tree and XOR tree for direct comparison. We demonstrate how XOR-based dSiPMs solve the limitation caused by monostable circuits and reach higher maximum count rates compared with optimized OR-based dSiPMs. The increased throughput of the SPAD array allows higher sampling rates for the digitization of the light signal enhancing dynamic range and linearity

A SPAD-Based QVGA Image Sensor for Single-Photon Counting and Quanta Imaging

A CMOS single-photon avalanche diode (SPAD)-based quarter video graphics array image sensor with 8-μm pixel pitch and 26.8% fill factor (FF) is presented. The combination of analog pixel electronics and scalable shared-well SPAD devices facilitates high-resolution, high-FF SPAD imaging arrays exhibiting photon shot-noise-limited statistics. The SPAD has 47 counts/s dark count rate at 1.5 V excess bias (EB), 39.5% photon detection probability (PDP) at 480 nm, and a minimum of 1.1 ns dead time at 1 V EB. Analog single-photon counting imaging is demonstrated with maximum 14.2-mV/SPAD event sensitivity and 0.06e- minimum equivalent read noise. Binary quanta image sensor (QIS) 16-kframes/s real-time oversampling is shown, verifying single-photon QIS theory with 4.6× overexposure latitude and 0.168e- read noise

Analysis of Photon Detection Efficiency and Dynamic Range in SPAD based Visible Light Receivers

We investigate the photon detection efficiency (PDE) and the dynamic range for digital silicon photomultipliers (dSiPMs) over a selection of design parameters: dSiPM unit cell dead time, PDE, unit cell area and fill factor, number of cells, and total dSiPM active area. Two receiver scaling scenarios are con-sidered: varying the number of cells for 1) a fixed unit cell area or 2) a fixed total dSiPM area. Theoretical and simulated results are confirmed with experimental data from a selection of dSiPMs realised on a test chip in130-nm CMOS process

A Simulation Model for Digital Silicon Photomultipliers

We propose a simulator model to estimate the performance of digital Silicon Photomultipliers (dSiPM) based on Single Photon Avalanche Diodes (SPADs) in terms of detection rate of photons incident on the sensor. The work provides guidelines for efficient array structure depending on: the number of SPADs, fill factor, area of both SPADs and array. A comparison of the main techniques present in the literature to digitally combine multiple outputs into single channel is included with simulated results showing promising higher detection rates for XOR-based dSiPMs. Mathematical expressions are derived to estimate dSiPM parameters such as maximum detection rate and detector dead time as functions of the mentioned design parameters

Analysis and optimisation of high throughput digital silicon photomultipliers

Large area detectors for time correlated single photon counting (TCSPC) are nowadays being implemented in CMOS technology to benefit a large variety of applications including positron emission tomography (PET) and 3D laser ranging (LiDAR), exploiting the advanced timing and counting capabilities inside single chips. Single photon avalanche diodes (SPADs) and silicon photomultipliers (SiPMs) represent a great option to realise such detectors thanks to their exceptional timing resolution and the ability to be arranged into arrays. Recently, digital SiPMs (dSiPMs) have been introduced to improve the integration with CMOS technology overcoming limitations on the readout of analogue SiPMs and thus improving the photon resolution of the detector. This work presents a 14GSamples=s time-to-digital converter (TDC) to improve the throughput of dSiPM sensors commonly limited by the sampling rate of the timing/counting readout circuitry. The converter has been demonstrated on a test chip in 130nm CMOS imaging technology paired with a novel XOR-based 32 32 SPAD array single-channel detector. The overall achieved throughput equals 1GEvents=s demonstrated in a direct time-of-flight LiDAR experiment. By acquiring a number of photons significantly higher than one per laser pulse, this approach represents the first example in TCSPC of an input rate and conversion rate both higher than the excitation rate. The following part of the work presents a modelling analysis on how to match the achieved high sampling rate / throughput of the single-channel TDC to the performance of a SPAD array. The impact of a selection of dSiPM design parameters, such as photon detection efficiency, dead time and size of the SPAD cell, number of cells per single-channel, digital N-to-1 combining network and channel bandwidth, on the overall sensor throughput and the dynamic range has been characterised thanks to a computational Monte-Carlo simulator and useful equations describing each of the processes in the sensing chain. The pile-up effect, i.e. the event-loss causing non-linear distortions on the output signal, has been characterised on each element of the dSiPM and optimisations have been proposed. Event losses in the SPAD cells due to dead time, in the digital combining network due to network dead time and single-channel bandwidth have all been identified, simulated and described by analytical equations. All the results coming from the theoretical analysis have been reproduced in real dSiPM design thanks to a reconfigurable test chip realised in the same 130nm CMOS imaging technology specifically to validate the proposed theory. The manufactured test chip provides the very first direct comparison between OR-based and XOR-based single-channel dSiPM sensors highlighting the promising timing and counting performance of the newly introduced XOR-based dSiPM. Direct evidence of pile-up distortions and subsequent reduction through design optimisations are demonstrated. A recommended design flow for next generation dSiPMs is proposed at the end of the publication

Long range LiDAR characterisation for obstacle detection for use by the visually impaired and blind

Obstacle detection and avoidance is a huge area of interest for autonomous vehicles and, as such, has become an important research topic. Detecting and identifying obstacles enables navigation through an ever changing environment. This work looks at the technology used in self-driving vehicles and examines whether the same technology could be used to aid in navigation for visually impaired and blind (VIB) people. For autonomous vehicles, obstacle detection relies on different sensor modalities to provide information on the vehicles surroundings. A combination of the same sensors placed on a white cane could be used to perform free-space assessment over the whole height of the user and provide additional environmental information not available from the cane alone. This provides its own challenges and advantages. The speeds are much slower when dealing with pedestrians and scanning can be achieved by the movement of the cane. However, the weight and size must be significantly reduced. The full system will be integrated into a smart cane and will consist of four main sensors as well as range sensors. The aim of this work is to report on the characterisation of a long range LiDAR (up to 10m) that will be integrated into a smart white cane developed as part of the INSPEX H2020 project

Long range LiDAR characterisation for obstacle detection for use by the visually impaired and blind

Obstacle detection has become a very important area of interest for the automotive industry due to the move towards autonomous vehicles. Since the environment the vehicle has to navigate is ever changing the current best system for obstacle detection is to combine a number of sensors. This means that for the varying weather and lighting conditions the best sensor can be used to provided obstacle detection and avoidance information. The INSPEX H2020 project goal is to use a similar system of multiple sensors to provide personal obstacle detection for visually impaired and blind (VIB) people. Figure 1 shows the INSPEX ambition. Power, weight and size reduction will be key to achieving this goal. In this paper the initial prototype is characterised and improvements beyond typical reduction of key parameters is considered. The INSPEX system will integrate a short range LiDAR (distances up to 5m), an ultrawide band (UWB) RADAR (distances up to 5m), ultrasound (distances up to 2m) and a long range LiDAR (distances up to 10m). The sensors will be miniaturised and the power consumption reduced so that they can be incorporated into a white cane. In this paper the first prototype for the long range LiDAR sensor is characterised for various lighting conditions and distances. The results show that for distances of 3m and 5m consistence obstacle detection can be achieved even in bright lighting conditions but for distances beyond this the detection can be inconsistence and is highly dependent on the lighting conditions