Experimental Moving Target Imaging in a Nonanechoic Environment With Linear Sampling Method

Dogu, Semih; Akıncı, Mehmet Nuri; Gose, Ersin

doi:10.1109/lgrs.2020.2976594

Cited by 14 publications

(8 citation statements)

References 15 publications

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“…e conducted analysis has also shown the existence of dominant harmonics, which have a major influence on the target reconstruction. Hence, utilizing only the dominant harmonics reduces the computational time with slight performance loss [41][42][43][44][45][46][47][48][49]…”

Section: Discussionmentioning

confidence: 99%

A Three-Dimensional Microwave Sparse Imaging Approach Using Higher-Order Basis Functions

Vojnovic

Crocco

Stevanovic

2022

International Journal of Antennas and Propagation

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This paper presents a novel method for three-dimensional microwave imaging based on sparse processing. To enforce the sparsity of the unknown function, we take advantage of the fact that arbitrary three-dimensional electromagnetic fields can be decomposed into two components with respect to the radial direction: one with transverse-magnetic polarization and the other with transverse-electric polarization. Each component can be further expressed as a sum of spherical harmonics, which provide the dictionary exploited by the sparse processing algorithm. Our measurement model relates the data and the parameters of the spherical harmonics’ sources, which are uniformly distributed on a grid sampling the imaging domain. By relying on the theory of degrees of freedom of electromagnetic fields, it can be shown that only a few harmonics are sufficient to accurately represent the measured scattered field from objects whose diameter is of the order of the wavelength, thus allowing reducing the dimension of the adopted dictionary. We analyze several imaging scenarios to assess the algorithm’s performance, including different object shapes, sensor orientations, and signal-to-noise ratios. Moreover, we compare the obtained results with other state-of-the-art linear imaging techniques. Notably, thanks to the adopted dictionary, the proposed algorithm can yield accurate images of both convex and concave objects.

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Section: Discussionmentioning

confidence: 99%

A Three-Dimensional Microwave Sparse Imaging Approach Using Higher-Order Basis Functions

Vojnovic

Crocco

Stevanovic

2022

International Journal of Antennas and Propagation

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“…Here, note that although the scattering problem is linear, when the scatterer is constant, the equation ( 16) is approximately true due to the ill-posedness of (6). Then, similarly define the superposed total field on the domain as:…”

Section: Relation Between Ssm Indicator and Electrical Parametersmentioning

confidence: 99%

“…Inverse electromagnetic (EM) scattering problems have been broadly investigated among researchers and have found many appearances in applied sciences with mainly focusing on biomedical imaging, through-the-wall imaging, moving target detection, concealed weapon detection, subsurface imaging and food imaging for quality analysis [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15].…”

Section: Introductionmentioning

confidence: 99%

Continuous Monitoring of Hyperthermia Treatment of Breast Tumors With Singular Sources Method

et al. 2023

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Qualitative microwave imaging methods provide a fast and accurate reconstruction of the shapes of the targets from scattered electric field measurements. In this paper, a qualitative imaging method, the singular sources method (SSM), is analyzed for two-dimensional transverse magnetic electromagnetic (2D-TM EM) inverse scattering scenarios. The contribution of the paper can be briefly summarized as: (i) The SSM was previously proposed for the far-field scenario, here we extend the SSM in the near field -inhomogeneous background setup. While making the extension each step (which includes an integral equation) is explained by exploiting the linearity and reciprocity principles to give physical insights. (ii) The relation between the electrical parameters of the scatterers and the indicator of SSM is derived. (iii) To analyze the performance of SSM in real-world problems, the proposed method is tested for monitoring hyperthermia treatment problems with a realistic breast model. Obtained results show that the SSM can handle realistic breast phantoms for monitoring hyperthermia problems.INDEX TERMS Hyperthermia treatment, inverse scattering, microwave imaging, singular sources method, temperature monitoring.

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“…The downside is the longer computational time compared to that of the TSVD. The linear sampling method (LSM) [43]- [45], also widely used for qualitative imaging, yielded poor results for considered scenarios due to the insufficient number of transmitters (the rank of the multistatic matrix was smaller than the number of significant singular values); hence, we have not included those results.…”

Section: Introductionmentioning

confidence: 99%

Smooth Polynomial Approach for Microwave Imaging in Sparse Processing Framework

2022

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We developed a novel qualitative imaging algorithm based on a polynomial approximation of the unknown contrast and sparse (l 1 ) regularization. Contrary to previously published results, we defined polynomial basis functions on subdomains that divide the investigation domain. Moreover, we formulated constraints that ensure the continuity of the contrast on subdomain borders. We showed that the proposed algorithm improved imaging resolution, particularly in multiple target scenarios. We demonstrated that partitioning the investigation domain together with contrast continuity formulation enhanced the numerical stability and reduced the computation time. The obtained results were significantly less sensitive to the regularization parameter values than those obtained using the standard polynomial approximation. Namely, smaller domains allow lower polynomial orders, which are numerically more favorable. Continuity constraints reduce the search space and mitigate the occurrence of false solutions. Another contribution of this study is a novel strategy for regularization parameter selection. We considered different figures of merit and numerical scenarios to study the influence of various parameters involved in the imaging process, such as the polynomial order and number of subdomains. An extensive analysis proved the robustness of the approach against noise. The proposed algorithm was designed for two-dimensional geometry. However, generalization to three-dimensional space is straightforward. The algorithm can also be used with other types of regularization such as the l 2 regularization. Potential applications include medical microwave imaging, in which high resolution and noise immunity are vital features.INDEX TERMS Inverse scattering, microwave imaging, polynomial approximation, and sparse processing.

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Experimental Moving Target Imaging in a Nonanechoic Environment With Linear Sampling Method

Cited by 14 publications

References 15 publications

A Three-Dimensional Microwave Sparse Imaging Approach Using Higher-Order Basis Functions

A Three-Dimensional Microwave Sparse Imaging Approach Using Higher-Order Basis Functions

Continuous Monitoring of Hyperthermia Treatment of Breast Tumors With Singular Sources Method

Smooth Polynomial Approach for Microwave Imaging in Sparse Processing Framework

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