Numerical and experimental assessment of a phase retrieval technique applied to planar near field distribution for wide band application

International audienceThe work presented in the following is devoted to the characterization of an harmonic source in a wide band of frequencies [0.5, 20 GHz] from the knowledge of the amplitude-only electric fields at near field measurement distance. Such a problem leads to the development of a “phase reconstruction” algorithm. In that paper a classical propagation/retro-propagation scheme has been applied. This is the first step of a study concerning the characterization of electromagnetic pulsed source from phaseless measurement techniques in near field conditions. The algorithm has been tested and validated using numerical and experimental data acquired at different frequencies and in different configurations

An Adaptive Multi-Scaling Imaging Technique Based on a Fuzzy-Logic Strategy for Dealing with the Uncertainty of Noisy Scattering Data

Inverse scattering data, even though collected in a controlled-environment, are usually corrupted by noise, which strongly affects the effectiveness of the reconstruction techniques because of the intrinsic ill-positioning of the problem. In order to limit the effects of the noise on the retrieval procedure and to fully exploit the information content available from the measurements, an innovative inversion scheme based on the integration of an adaptive multiscale procedure and a fuzzy-logic (FL)-based strategy is proposed. The main goal of the approach is to reduce the complexity of the problem as well as to improve the robustness of the inversion procedure allowing an accurate retrieval of the profile under test. The approach is based on an adaptive, coarse-to-fine successive representation of the unknown object obtained through a sequence of reconstructions where suitable weighting coefficients are defined through a FL. Key elements of the theoretical analysis are given and several numerical examples, concerned with synthetic and experimental test cases, illustrate the consequences of the proposed approach in terms of both resolution accuracy and robustness as well as computational costs. (c) 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works

Fuzzy-Logic Reasoning for Estimating the Reliability of Noisy Data in Inverse Scattering Problems

Inverse scattering data, even though collected in a controlled environment, are usually corrupted by electromagnetic noise, which strongly affects the effectiveness of the reconstruction techniques because of the intrinsic ill-positioning of the problem. In order to limit the effects of the noise on the retrieval procedure and to fully exploit the limited information content available from the measurements, an innovative inversion scheme based on the integration of an adaptive multi-scale procedure and a fuzzy-logic-based decision strategy is proposed. The approach is based on an adaptive, coarse-to-fine successive representation of the unknown object obtained through a sequence of nonlinear reconstructions where suitable weighting coefficients are defined using fuzzy logic. Numerical examples from synthetic and experimental test cases are given to illustrate the advantages brought by the proposed approach in terms of reconstruction quality

Assessment of the Reliability and Exploitation of the Information Content of Inverse Scattering Data through a Fuzzy-Logic-Based Strategy - Preliminary Results

The presence of the noise in the measured data should be carefully considered in inverse scattering methodologies, because of the intrinsic ill-conditioning of the problem. To limit the effects of the noise on the retrieval procedure, this paper presents an innovative fuzzy-logic-based approach. The proposed strategy allows one to take into account the corrupted nature of the data by fully exploiting all the available information content of the measurements. Selected synthetic and experimental test cases are considered for assessing the effectiveness of the proposed approach also in comparison with a reference inverse scattering technique

Enhancement of the Contrast Source Inversion Method Using Fuzzy Logic

The problem of determining the proprieties of an unknown object by means of electromagnetic waves probing the object is intrinsically instable with respect to the presence of noise and measurement errors on scattering data. In several practical condition in the framework of medical imaging, non-destructive testing, and sub-surface inspection, these errors are unavoidable and the ill-posedness of the system leads to inaccurate reconstructions of the scenario under test. In [1], an innovative fuzzy-logic-based strategy has been proposed for properly taking into account the presence of the noise and errors on the data. Such a system provides, in an unsupervised way, two series of coefficients that can be used as weighting parameters of the arising cost function to be minimized. In that paper, the mathematical formulation was presented considering the contrast and the fields equations. In this work, a further assessment of the proposed fuzzy-logic approach is carried out operating with data and state equations expressed in terms of the contrast and the contrast sources as suggested in [2]. Selected results from the numerical simulations are reported to assess the performances of the system with single and multi-frequency data with and without total-variation-based regularization. This is the author's version of the final version available at IEEE

Effective Exploitation of the Information Content of Noisy Data in Inverse Scattering Problems: a Fuzzy-Logic-Based Strategy

One of the main drawbacks when dealing with inverse scattering problems is their intrinsic ill-conditioned nature, emphasized by the presence of the noise in the measured data. The proposed fuzzy system allows to take into account the corrupted nature of the data in a simple and effective way. The effectiveness of the proposed inversion strate4gy is shown by comparing the achieved results with those obtained with state-of-the art inverse scattering techniques

An Innovative Fuzzy-Logic-Based Strategy for an Effective Exploitation of Noisy Inverse Scattering Data

This paper presents an innovative inverse scattering approach based on a fuzzy-logic strategy aimed at fully exploiting the information content of the scattered data in a microwave imaging system. The effectiveness of the proposed method is assessed through the results of a numerical analysis concerned with the reconstruction of single as well as multiple dielectric targets in various noisy environments. For comparison purposes, the obtained performance are compared with those of a standard method in terms of reconstruction accuracy and computational load to point out the improvement induced by the proposed approach

Integration of a Fuzzy Logic System With the Contrast Source Inversion Method: A Numerical Validation

In this work, selected results from extensive numerical simulations will be presented to assess the performances of an integrated inversion scheme based on the CSI method and the Fuzzy Logic Systems. The results will also highlight the interaction effects between the fuzzy regularization coefficients and the regularization approach based on the total variation for both single and multiple-frequency data sets