Iterative regularization method for lidar remote sensing
- In this paper we present an inversion algorithm for ill-posed problems arising in atmospheric remote sensing. The proposed method is an iterative Runge-Kutta type regularization method. Those methods are better well known for solving differential equations. We adapted them for solving inverse ill-posed problems. The numerical performances of the algorithm are studied by means of simulations concerning the retrieval of aerosol particle size distributions from lidar observations.
Author details: | Christine BöckmannORCiDGND, Andreas KirscheGND |
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URL: | http://www.sciencedirect.com/science/journal/00104655 |
DOI: | https://doi.org/10.1016/j.cpc.2005.12.019 |
ISSN: | 0010-4655 |
Publication type: | Article |
Language: | English |
Year of first publication: | 2006 |
Publication year: | 2006 |
Release date: | 2017/03/24 |
Source: | Computer physics communications. - ISSN 0010-4655. - 174 (2006), 8, S. 607 - 615 |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Mathematik |
Peer review: | Referiert |