Iteratively regularized Gauss-Newton method for atmospheric remote sensing
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.
regularization remote sensing inverse problems nonlinear least squares atmospheric spectroscopy