In this paper, a new approach for the quantitative electromagnetic imaging of unknown scatterers located in free space from amplitude-only measurements of the total field is proposed and discussed. The reconstruction procedure splits the problem into two steps. The method is based on the use of an inverse source algorithm to first complete the scattering data by estimating the distribution of the radiated field in the investigation domain. The object's function profile is then retrieved from the phaseless data via an iterative multiresolution procedure integrated with an effective minimization technique based on the particle swarm algorithm. Numerical examples are provided to assess the effectiveness of the whole two-step strategy in the presence of synthetic noise-corrupted data as well as in dealing with experimental data sets. Comparisons with full-data and bare" approaches are reported as well. (c) 2006 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users
Inversion of Phaseless Total Field Data using a Two-Step Strategy based on the Iterative Multi-Scaling Approach / Donelli, Massimo; Azaro, Renzo; Franceschini, Gabriele; Massa, Andrea. - ELETTRONICO. - (2006), pp. 1-48.
Inversion of Phaseless Total Field Data using a Two-Step Strategy based on the Iterative Multi-Scaling Approach
Donelli, Massimo;Azaro, Renzo;Franceschini, Gabriele;Massa, Andrea
2006-01-01
Abstract
In this paper, a new approach for the quantitative electromagnetic imaging of unknown scatterers located in free space from amplitude-only measurements of the total field is proposed and discussed. The reconstruction procedure splits the problem into two steps. The method is based on the use of an inverse source algorithm to first complete the scattering data by estimating the distribution of the radiated field in the investigation domain. The object's function profile is then retrieved from the phaseless data via an iterative multiresolution procedure integrated with an effective minimization technique based on the particle swarm algorithm. Numerical examples are provided to assess the effectiveness of the whole two-step strategy in the presence of synthetic noise-corrupted data as well as in dealing with experimental data sets. Comparisons with full-data and bare" approaches are reported as well. (c) 2006 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other usersFile | Dimensione | Formato | |
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