In direct time-of-flight (D-TOF) light detection and ranging (LIDAR), accuracy and full-scale range (FSR) are the main performance parameters to consider. Particularly, in single-photon avalanche diodes (SPAD) based systems, the photon-counting statistics plays a fundamental role in determining the LIDAR performance. Also, the intrinsic performance ultimately depends on the system parameters and constraints, which are set by the application. However, the best-achievable performance directly depends on the selected depth estimation method and is not necessarily equal to intrinsic performance. We evaluate a D-TOF LIDAR system, in the particular context of smartphone applications, in terms of parameter trade-offs and estimation efficiency. First, we develop a simulation model by combining radiometry and photon-counting statistics. Next, we perform a trade-off analysis to study dependencies between system parameters and application constraints, as well as non-linearities caused by the detection method. Further, we derive an analytical model to calculate the Cramér–Rao lower bound (CRLB) of the LIDAR system, which analytically accounts for the shot noise. Finally, we evaluate a depth estimation method based on artificial intelligence (AI) and compare its performance to the CRLB. We demonstrate that the AI-based estimator fully compensates the non-linearity in depth estimation, which varies depending on application conditions such as target reflectivity.

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This paper presents our latest results from the investigation of the surface oxide content in boron capped layers used as the entrance window in ultraviolet silicon (UV-Si) photodetectors. These photodetectors have been studied electrically and optically to define the correlation between oxide content and performance, i.e. the direct relationship between the amount of undesired surface oxide in the active region where the boron layer is deposited, and the detector stability to high UV exposure levels. The boron capping layers were deposited by either chemical or physical vapor based deposition techniques (CVD or PVD). Although these techniques provide photodetectors that are highly sensitive to UV radiation [1], the formation of surface oxide during deposition is a major concern, especially for stability. To analyze the oxide content, an XPS (X-ray photoelectron spectroscopy) analysis was performed on high-temperature (HT-CVD: 700 °C), low-temperature (LT-CVD: 400 °C), and room-temperature (RT-CVD: 25 °C) based pure boron (PureB) photodetectors. An inverse relationship between deposition temperature and oxide content was noticed. While the HT-CVD based photodetectors were found to contain 30% of oxide in its active region, this amount drops to less than 10% for LT-CVD, and to a few percent for RT-PVD based process.@en