Optimization of System Design and Calibration Algorithm for SPAD-Based LiDAR Imager

This article presents the optimization of system design and calibration algorithm for light detection and ranging (LiDAR) imager based on the single-photon avalanche diode (SPAD) image sensor. The supply voltage and the gating high-voltage driving circuit of the SPAD are optimized based on the theoretical analysis and experimental data to improve the trigger times of the SPAD for the laser echo. The real-time calibration algorithm is realized in a field-programmable gate array (FPGA) to obtain the flight time and improve the measurement reliability. A 10-bit time- and area-efficient shifted interframe multievent histogram and a bubbling-based peak detection algorithm are used to calculate flight time, which requires the memory as low as 16 times smaller than storing complete histogram if the pixel values are coded on up to 10 bits and can detect up to four different targets simultaneously without increasing the measurement time. The performance of different kinds of background noise measurement methods is analyzed based on experimental data, which shows that the measurement results are more accurate with the increase of time-to-digital converter (TDC) event detection ability. The proposed crosstalk suppression algorithm based on the LiDAR transmission function can reduce optical crosstalk between adjacent pixels to improve the measurement reliability of the LiDAR imager. The LiDAR imager is presented as capable of measuring a 10-m range with 70-Klux background noise and a
$30^{\circ } \times 45^{\circ }$
field of view.