An entire solid-state direct time-of-flight (dToF) light detection and ranging (LiDAR) system that incorporates innovations for both the transmitter (TX) and the receiver (RX) is presented in this work. For the illumination TX, we demonstrate solid-state channel addressability, which significantly reduces the transmit power and improves the ranging distance by dividing the field of view (FoV) into separately illuminated sub-regions. In the RX, we introduce single-photon avalanche diodes (SPADs) pixel binning, which enables reconfigurability of the sensor’s spatial resolution. Finally, we introduce a machine learning (ML) technique that enables this pixel-binned depth sensor to upscale its spatial resolution after training/inference fusion with the intensity image. The laser diode driver (LDD) chip is implemented in the 180-nm bipolar-CMOS-DMOS (BCD) process and is capable of pumping more than 8-A peak current into a multi-junction vertical-cavity surface-emitting laser (VCSEL) array, producing up to 20.3-W optical pulses under 12.5-V supply voltage. The sensor chip is also implemented in the 180-nm BCD process with a $128 \times 128$ SPAD array and reconfigurable pixel binning. Hardware and software co-optimization under low signal-to-noise ratio (SNR) conditions with ML-based spatial resolution upscaling is demonstrated.

The applications requiring three-dimensional information have been growing rapidly, including facial recognition, gesture recognition, auto-focus for 2D camera, self-driving autonomous vehicles, etc. Indirect Time-of-Flight (iToF) technique has been adopted widely for 3D depth imaging due to its high spatial resolution and excellent depth accuracy performance. In this paper, a 200 MHz pulsed optical Illuminator for iToF applications is reported. A 940 nm GaAs-based triple-junction VCSEL array is adopted and an integrated pulsed VCSEL driver ASIC in 180 nm BCD process is realized. Optical pulses with peak power up to 14 W can be transmitted by the laser illuminator with a maximum driving current of 6.5 A by the driver ASIC. The modulation frequency can be up to 200 MHz. Automatic optical power control (AOPC) is realized for stable optical power output and laser eye safety protection. An on-chip DLL-based time interpolator is proposed to eliminate the mechanical moving components used during system calibration. The measured absolute accuracy of the time interpolator is +/-50 ps with a resolution of 800 ps and tuning range of 49.6 ns. This work effectively extends the measurement distance of the iToF system. The calibration efficiency is also improved with the proposed method.

An integrated laser diode driver for multi-junction vertical-cavity surface-emitting laser (VCSEL) arrays is presented in this brief. The driver chip, fabricated in 180nm bipolar-CMOS-DMOS (BCD) process, working under 12V supply, can pump more than 8A peak current into a triple-junction VCSEL array, producing up to 20.3W optical pulses. Measured optical pulses have tunable widths from 276ps to 2352ps with 120ps/160ps rise/fall time. When emitting 10MHz-frequency 960ps-width optical pulses with peak power ranging from 3.6W to 17.5W, the driver-VCSEL system has over 20% electrical-to-optical power conversion efficiency. The driver can record its output current waveform with a built-in pulse monitor. The peak data from the recorded waveform is used for automatic peak current control.

Light Detection and Ranging (LiDAR) is becoming a critical requirement for future computer vision applications, such as AR/VR (iPhone-LiDAR) and ADAS (Automotive-LiDAR). A depth point-cloud input has different characteristics than a conventional RGB image input, such that the CNN depthinference implementation is unique when compared with a standard super-resolution CNN(SR-CNN). In this brief, we present a heterogeneous AI-accelerator SoC, which is specific to depth image completion computation. Three key innovations are introduced to improve SoC’s performance. First, to accommodate the unique input data structure of a depth input, a fully-filled dataflow management engine is proposed to pre-process the RGB+Depth input, significantly improving processing element utilization (PEU). Second, to improve the efficiency of the instruction configurations of the CNN accelerator, a hardware-tiling co-processor is proposed that performs the tiling strategy of the CNN accelerator, assigning each sub-job to the PE array directly, therefore reducing the time for task assignments. Third, due to the large number of vector operations required for the postprocess in the neural network, a RISC-V core is incorporated to execute vector computations better. The SoC is implemented in 40nm CMOS process, achieving 2TOPs/W energy efficiency with 34fps throughput under VGA-resolution output for realtime LiDAR systems.

LiDAR (Light Detection and Ranging) imaging based on SPAD (Single-Photon Avalanche Diode) technology suffers from severe area penalty for large on-chip histogram peak detection circuits required by the high precision of measured depth values. In this work, a probabilistic estimation-based super-resolution neural network for SPAD imaging that firstly uses temporal multi-scale histograms as inputs is proposed. To reduce the area and cost of on-chip histogram computation, only part of the histogram hardware for calculating the reflected photons is implemented on a chip. On account of the distribution rule of returned photons, a probabilistic encoder as a part of the network is first proposed to solve the depth estimation problem of SPADs. By jointly using this neural network with a super-resolution network, 16× up-sampling depth estimation is realized using 32 × 32 multi-scale histogram outputs. Finally, the effectiveness of this neural network was verified in the laboratory with a 32 × 32 SPAD sensor system.

This letter presents a novel fully integrated dToF system-on-chip ranging sensor based on a SPADs array. The sensor is made a configurable array of $16\times16$ SPADs, a 940nm VCSEL, a co-design VCSEL driver and embedded DSP core. To suitable different ranging scenarios with high reliability and low cost, the above mentioned are all packaged into one module for ranging. However, the package of coverglass can cause Xtalk, which have a negative impact on ranging. In order to reduce the influence of Xtalk on ranging. This letter proposes a real-time Xtalk calibration circuit system, which can automatically adjust the laser pulse width, when Xtalk and target bins are mixed together. And also to mitigate the effect of SPAD jitter on the Xtalk bins width, an adjustable bias voltage charge pump circuit is adopted to realize the accurate adjustment of pixel SPAD’s bias voltage. The system has been turned out with precision of better than 5mm within 6m in 80% reflectance of target, still with a precision better than 8mm at a distance within 4m in 18% reflectance of target.