Iteratively regularized Gauss-Newton method for atmospheric remote sensing

被引：37

作者：

Doicu, A ^{[1
]}

Schreier, F ^{[1
]}

Hess, M ^{[1
]}

机构：

[1] DLR, German Aerosp Ctr, Remote Sensing Technol Inst, D-82234 Wessling, Germany

来源：

COMPUTER PHYSICS COMMUNICATIONS | 2002年 / 148卷 / 02期

关键词：

inverse problems; nonlinear least squares; regularization; atmospheric spectroscopy; remote sensing;

D O I：

10.1016/S0010-4655(02)00555-6

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this paper we present an inversion algorithm for nonlinear ill-posed problems arising in atmospheric remote sensing. The proposed method is the iteratively regularized Gauss-Newton method. The dependence of the performance and behaviour of the algorithm on the choice of the regularization matrices and sequences of regularization parameters is studied by means of simulations. A method for improving the accuracy of the solution when the identity matrix is used as regularization matrix is also discussed. Results are presented for atmospheric temperature retrievals from a far infrared spectrum observed by an airborne uplooking heterodyne instrument. (C) 2002 Elsevier Science B.V. All rights reserved.

引用

页码：214 / 226

页数：13

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