Ai, Xiao, PÉREZ-SERRANO, A, Quatrevalet, M, Nock, Richard, Dahnoun, Naim, Ehret, G, ESQUIVIAS, I and Rarity, John (2016). Analysis of a random modulation single photon counting differential absorption lidar system for space-borne atmospheric CO2 sensing. Optics Express, 24 (18), pp. 21119-21133.
Abstract
The ability to observe the Earth’s carbon cycles from space provides scientists an important tool to analyze climate change. Current proposed systems are mainly based on pulsed integrated path differential absorption lidar, in which two high energy pulses at different wavelengths interrogate the atmosphere sequentially for its transmission properties and are back-scattered by the ground. In this work an alternative approach based on random modulation single photon counting is proposed and analyzed; this system can take advantage of a less power demanding semiconductor laser in intensity modulated continuous wave operation, benefiting from a better efficiency, reliability and radiation hardness. Our approach is validated via numerical simulations considering current technological readiness, demonstrating its potential to obtain a 1.5 ppm retrieval precision for 50 km averaging with 2.5 W average power in a space-borne scenario. A major limiting factor is the ambient shot noise, if ultra-narrow band filtering technology could be applied, 0.5 ppm retrieval precision would be attainable.
Publication DOI: | https://doi.org/10.1364/OE.24.021119 |
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Divisions: | College of Engineering & Physical Sciences > Adaptive communications networks research group College of Engineering & Physical Sciences |
Additional Information: | Published by The Optical Society under the terms of the Creative Commons Attribution 4.0 License. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. |
Publication ISSN: | 1094-4087 |
Last Modified: | 26 Aug 2024 08:38 |
Date Deposited: | 09 Jan 2019 13:32 | PURE Output Type: | Article |
Published Date: | 2016-09-01 |
Accepted Date: | 2016-08-08 |
Authors: |
Ai, Xiao
PÉREZ-SERRANO, A Quatrevalet, M Nock, Richard ( ![]() Dahnoun, Naim Ehret, G ESQUIVIAS, I Rarity, John |