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A Linear Method for Shape Reconstruction Based on the Generalized Multiple Measurement Vectors Model

Year: 2018

Type: article

Abstract: In this paper, a novel linear method for shape reconstruction is proposed based on the generalized multiple measurement vectors' (GMMVs) model. Finite-difference frequency domain is applied to discretize Maxwell's equations, and the contrast sources are solved iteratively by exploiting the joint sparsity as a regularized constraint. Cross validation technique is used to terminate the iterations, such that the required estimation of the noise level is circumvented. The validity is demonstrated with an excitation of transverse magnetic experimental data, and it is observed that, in the aspect of focusing performance, the GMMV-based linear method outperforms the extensively used linear sampling method.

Source: IEEE Transactions on Antennas and Propagation

DOI: 10.1109/tap.2018.2806404

Authors: Shilong Sun, Bert Jan Kooij, Alexander G. Yarovoy, Tian Jin

Institutions: Delft University of Technology, National University of Defense Technology

Language: English

Topic: Microwave Imaging and Scattering Analysis

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2790127798

FWCI: 0.473

Cites: 53

Cited by: 12

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