Garbarino, S;
Sorrentino, A;
Massone, AM;
Sannino, A;
Boselli, A;
Wang, X;
Spinelli, N;
(2016)
Expectation maximization and the retrieval of the atmospheric extinction coefficients by inversion of Raman lidar data.
Optics Express
, 24
(19)
pp. 21497-21511.
10.1364/OE.24.021497.
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Abstract
We consider the problem of retrieving the aerosol extinction coefficient from Raman lidar measurements. This is an ill–posed inverse problem that needs regularization, and we propose to use the Expectation–Maximization (EM) algorithm to provide stable solutions. Indeed, EM is an iterative algorithm that imposes a positivity constraint on the solution, and provides regularization if iterations are stopped early enough. We describe the algorithm and propose a stopping criterion inspired by a statistical principle. We then discuss its properties concerning the spatial resolution. Finally, we validate the proposed approach by using both synthetic data and experimental measurements; we compare the reconstructions obtained by EM with those obtained by the Tikhonov method, by the Levenberg-Marquardt method, as well as those obtained by combining data smoothing and numerical derivation.
| Type: | Article |
|---|---|
| Title: | Expectation maximization and the retrieval of the atmospheric extinction coefficients by inversion of Raman lidar data |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1364/OE.24.021497 |
| Publisher version: | https://doi.org/10.1364/OE.24.021497 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Science & Technology, Physical Sciences, Optics, Elastic-backscatter Lidar, Planetary Boundary-layer, Aerosol Extinction, Earlinet Project, Particle Parameters, Profiles, Framework, Algorithm, Ratio, Regularization |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1531426 |
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