In this paper, we propose and analyze two new direct factorization methods for solving inverse scattering problems. Both direct factorization methods are built upon the mathematically justified factorization method developed by Kirsch. The first one is naturally derived from a recent direct sampling method by replacing the corresponding far-field operator F in the indicator function by the factorized far-field operator (F * F) 1/4 . The second one is based on a truncated Neumann series approximation of the inverse of an appropriately scaled factorized far-field operator. Both direct factorization methods are shown to be stable with respect to noise and mathematically equivalent. Numerical results with both synthetic and real experimental data are presented to illustrate the promising accuracy of our proposed direct factorization methods in comparison to Kirsch's factorization method and the direct sampling method.

SUMMARYMeshfree discretizations construct approximate solutions to partial differential equation based on particles, not on meshes, so that it is well suited to solve the problems on irregular domains. Since the nodal basis property is not satisfied in meshfree discretizations, it is difficult to handle essential boundary conditions. In this paper, we employ the Lagrange multiplier approach to solve this problem, but this will result in an indefinite linear system of a saddle point type. We adapt a variation of the smoothed aggregation AMG method of Vaněk, Mandel & Brezina to this saddle point system. We give numerical results showing that this method is practical and competitive with other methods with convergence rates that are ∼ c/ log N .

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