Iteratively regularized Gauss–Newton method for atmospheric remote sensing
نویسندگان
چکیده
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. 2002 Elsevier Science B.V. All rights reserved. PACS: 02.60.Pn; 02.50; 07.05.Kf; 42.68.W
منابع مشابه
Pii: S0022-4073(02)00292-3
In this paper we present di0erent 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 pro...
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