A 65-nm CMOS Machine-Learning-Enhanced Bandwidth-Efficient LiDAR https://sscs.ieee.org/wp-content/themes/movedo/images/empty/thumbnail.jpg 150 150 https://secure.gravatar.com/avatar/8fcdccb598784519a6037b6f80b02dee03caa773fc8d223c13bfce179d70f915?s=96&d=mm&r=g
Abstract:
We present a proof-of-concept light detection and ranging (LiDAR) signal processing architecture that integrates a machine-learning-enhanced processing unit (PU) with on-chip time-to-digital converters (TDCs) to reduce bandwidth and memory requirements in SPAD-based direct time-of-flight (dToF) systems. The proposed architecture fits a Gaussian mixture model (GMM) to photon arrival time distributions …