We demonstrated a transceiver system for underwater three-dimensional imaging, based on a 64 × 32 macro-pixel direct time-of-flight (dToF) SPAD detector array fabricated using complementary metal-oxide-semiconductor (CMOS) technology. The sensor featured integrated multi-event time-to-digital converters (METDC) per macro-pixel, and operated in a time-gated mode which allowed the improved rejection of the backscattering from the signal return. The performance of the system was assessed in a controlled underwater environment, utilizing a moving target placed in a water tank at a stand-off distance of 1.45 m in water. The system demonstrated rapid 3D imaging by using short acquisition times of 1 ms, which corresponds to a frame rate of 1000 fps. Depth and intensity profiles were obtained at attenuation levels equivalent up to 5.5 attenuation lengths between the transceiver and the target, and using average optical power of up to 32 mW.
KEYWORDS: Single photon avalanche diodes, Data modeling, Systems modeling, Target recognition, LIDAR, Image segmentation, Image resolution, Time of flight imaging, Super resolution, Statistical modeling
We present a theoretical and computational model for simulating Single-Photon Avalanche Diode (SPAD) array images in the context of time-of-flight Lidar. We confirm the accuracy of out model by experimental verification. Further, we demonstrate that our simulated data can be used to train bespoke neural networks facilitating a number of enhanced imaging capabilities including, super-resolution, human-activity recognition, and long range SPAD Lidar.
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