Doicu, Adrian and Schreier, Franz and Hess, Michael (2004) Iterative regularization methods for atmospheric remote sensing. Journal of Quantitative Spectroscopy & Radiative Transfer, 83 (1), pp. 47-61.
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In this paper we present different inversion algorithms for nonlinear ill-posed problems arising in atmosphere remote sensing. The proposed methods are Landweber's method (LwM), the iteratively regularized Gauss-Newton method, and the conventional and regularizing Levenberg-Marquardt method. In addition, some accelerated LwMs and a technique for smoothing the Levenberg-Marquardt solution are proposed. The numerical performance of the methods is studied by means of simulations. Results are presented for an inverse problem in atmospheric remote sensing, i.e., temperature sounding with an airborne uplooking high-resolution far-infrared spectrometer.
|Title:||Iterative regularization methods for atmospheric remote sensing|
|Journal or Publication Title:||Journal of Quantitative Spectroscopy & Radiative Transfer|
|In ISI Web of Science:||Yes|
|Page Range:||pp. 47-61|
|Keywords:||Inverse problems; Nonlinear least squares; Regularization; Atmospheric spectroscopy; Remote sensing|
|HGF - Research field:||Aeronautics, Space and Transport (old)|
|HGF - Program:||Space (old)|
|HGF - Program Themes:||W EO - Erdbeobachtung|
|DLR - Research area:||Space|
|DLR - Program:||W EO - Erdbeobachtung|
|DLR - Research theme (Project):||UNSPECIFIED|
|Institutes and Institutions:||Remote Sensing Technology Institute|
|Deposited By:||elib DLR-Beauftragter|
|Deposited On:||25 Jan 2006|
|Last Modified:||06 Jan 2010 21:16|
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