Time-correlated single-photon counting (TCSPC) is a powerful optical technique, which permits recording fast luminous signals with picosecond precision. Unfortunately, given its repetitive nature, TCSPC is recognized as a relatively slow technique, especially when a large time-resolved image has to be recorded. In recent years, there has been a fast trend toward the development of TCPSC imagers. Unfortunately, present systems still suffer from a trade-off between number of channels and performance. Even worse, the overall measurement speed is still limited well below the saturation of the transfer bandwidth toward the external processor. We present a routing algorithm that enables a smart connection between a 32×32 detector array and five shared high-performance converters able to provide an overall conversion rate up to 10 Gbit/s. The proposed solution exploits a fully digital logic circuit distributed in a tree structure to limit the number and length of interconnections, which is a major issue in densely integrated circuits. The behavior of the logic has been validated by means of a field-programmable gate array, while a fully integrated prototype has been designed in 180-nm technology and analyzed by means of postlayout simulations.
We investigate the reconstruction of depth and intensity profiles from data acquired using a custom-designed time-of-flight scanning transceiver based on the time-correlated single-photon counting technique. The system had an operational wavelength of 1550 nm and used a Peltier-cooled InGaAs/InP single-photon avalanche diode detector. Measurements were made of human figures, in plain view and obscured by camouflage netting, from a stand-off distance of 230 m in daylight using only submilliwatt average optical powers. These measurements were analyzed using a pixelwise cross correlation approach and compared to analysis using a bespoke algorithm designed for the restoration of multilayered three-dimensional light detection and ranging images. This algorithm is based on the optimization of a convex cost function composed of a data fidelity term and regularization terms, and the results obtained show that it achieves significant improvements in image quality for multidepth scenarios and for reduced acquisition times.
The availability of compact, low-cost, and high-speed MEMS-based spatial light modulators has generated widespread interest in alternative sampling strategies for imaging systems utilizing single-pixel detectors. The development of compressed sensing schemes for real-time computational imaging may have promising commercial applications for high-performance detectors, where the availability of focal plane arrays is expensive or otherwise limited. We discuss the research and development of a prototype light detection and ranging (LiDAR) system via direct time of flight, which utilizes a single high-sensitivity photon-counting detector and fast-timing electronics to recover millimeter accuracy three-dimensional images in real time. The development of low-cost real time computational LiDAR systems could have importance for applications in security, defense, and autonomous vehicles.
Using time-correlated single photon counting for the purpose of fluorescence lifetime measurements is usually limited in speed due to pile-up. With modern instrumentation, this limitation can be lifted significantly, but some artifacts due to frequent merging of closely spaced detector pulses (detector pulse pile-up) remain an issue to be addressed. We propose a data analysis method correcting for this type of artifact and the resulting systematic errors. It physically models the photon losses due to detector pulse pile-up and incorporates the loss in the decay fit model employed to obtain fluorescence lifetimes and relative amplitudes of the decay components. Comparison of results with and without this correction shows a significant reduction of systematic errors at count rates approaching the excitation rate. This allows quantitatively accurate fluorescence lifetime imaging at very high frame rates.