Monte Carlo modeling and optimization of SPAD arrays for spaceborne LiDAR applications

Spaceborne LiDARs have long been used to investigate the Earth’s atmosphere, glaciers, and canopies, historically relying on photomultiplier tubes and avalanche photodiodes. Recently, attention has expanded to ocean ecosystems, imposing new challenges for the next generation of LiDAR instruments. In this context, Single-Photon Avalanche Diode (SPAD) arrays represent a promising alternative to conventional photodetectors, as they combine single-photon sensitivity, picosecond-level temporal resolution, and high dynamic range. To define the optimal SPAD array architecture and manage the associated design trade-offs, we developed a Monte Carlo model to predict device operation at the single-pixel level, including the dominant noise mechanisms. The proposed tool enables accurate prediction of the array response under varying incident photon fluxes and provides quantitative design guidelines for architecture optimization.