Simulating single-photon detector array sensors for depth imaging
This work addresses the need for efficient performance evaluation of SPAD array sensors, which are crucial for autonomous systems, by providing a simulation tool that could reduce testing costs.
The authors tackled the problem of predicting depth image quality from Single-Photon Avalanche Detector (SPAD) arrays under real-world conditions, developing a numerical procedure that rapidly establishes fundamental limits and generates realistic depth images without costly field testing.
Single-Photon Avalanche Detector (SPAD) arrays are a rapidly emerging technology. These multi-pixel sensors have single-photon sensitivities and pico-second temporal resolutions thus they can rapidly generate depth images with millimeter precision. Such sensors are a key enabling technology for future autonomous systems as they provide guidance and situational awareness. However, to fully exploit the capabilities of SPAD array sensors, it is crucial to establish the quality of depth images they are able to generate in a wide range of scenarios. Given a particular optical system and a finite image acquisition time, what is the best-case depth resolution and what are realistic images generated by SPAD arrays? In this work, we establish a robust yet simple numerical procedure that rapidly establishes the fundamental limits to depth imaging with SPAD arrays under real world conditions. Our approach accurately generates realistic depth images in a wide range of scenarios, allowing the performance of an optical depth imaging system to be established without the need for costly and laborious field testing. This procedure has applications in object detection and tracking for autonomous systems and could be easily extended to systems for underwater imaging or for imaging around corners.