Enhancing LIDAR performance metrics using continuous-wave photon-pair sources

Autor: Duncan G. England, Daniel Giovannini, Haoyu He, Han Liu, Benjamin J. Sussman, Amr S. Helmy, Bhashyam Balaji
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Popis: In order to enhance LIDAR performance metrics such as target detection sensitivity, noise resilience and ranging accuracy, we exploit the strong temporal correlation within the photon pairs generated in continuous-wave pumped semiconductor waveguides. The enhancement attained through the use of such non-classical sources is measured and compared to a corresponding target detection scheme based on simple photon-counting detection. The performances of both schemes are quantified by the estimation uncertainty and Fisher information of the probe photon transmission, which is a widely adopted sensing figure of merit. The target detection experiments are conducted with high probe channel loss (\(\simeq 1-5\times10^{-5}\)) and formidable environment noise up to 36 dB stronger than the detected probe power of \(1.64\times 10^{-5}\) pW. The experimental result shows significant advantages offered by the enhanced scheme with up to 26.3 dB higher performance in terms of estimation uncertainty, which is equivalent to a reduction of target detection time by a factor of 430 or 146 (21.6 dB) times more resilience to noise. We also experimentally demonstrated ranging with these non-classical photon pairs generated with continuous-wave pump in the presence of strong noise and loss, achieving \(\approx\)5 cm distance resolution that is limited by the temporal resolution of the detectors.
Databáze: OpenAIRE