A Sparse-Event Simulation Engine to Model Coincidence-Based Ranging Architectures in Quantum Lidar

Nonclassical radar and lidar systems have received substantial interest recently; however, although many experimental demonstrations have provided deep physical knowledge of such systems, there remains a lack of effective system models to obtain fundamental metrics such as range resolution as a function of system parameters. This work introduces a high-fidelity simulation platform to mimic a certain type of quantum radar, specifically a recently proposed one based on temporal coincidences that arise due to entanglement. Specifically, the system measures coincidences between events related to a reference source and those related to the backscattering of photons from targets. The large number of events—and their complex interaction with system components—makes a realistic simulation challenging. As an initial assessment, in this article, we develop a simulator to estimate the expected point spread function (PSF), and thereby the range resolution, considering various coincidence window time widths and system nonidealities. The estimate is based on the numerical computation of the correlation between the reference traces shifted along the time domain and traces of backscattered photons (along with noise photons). The simulated results are comparable to available experimental results, illustrating the fidelity of the simulation engine. A crucial result is that, unlike a classical radar, the PSF and range resolution depend upon the environmental noise and multiple system parameters, not just the transmitted waveform.