Image-Domain Estimation of Wall Parameters for Autofocusing of Through-the-Wall SAR Imagery

Jin, Tian; Chen, Bin; Zhou, Zhimin

doi:10.1109/tgrs.2012.2206395

Cited by 98 publications

(48 citation statements)

References 24 publications

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“…There are various methods of mitigating such wall clutter [2][3][4]. In this paper, we adopt the subspace projection method.…”

Section: Wall Clutter Mitigationmentioning

confidence: 99%

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Target-to-Clutter Ratio Enhancement of Images in Through-the-Wall Radar Using a Radiation Pattern-Based Delayed-Sum Algorithm

Lim¹,

Nam²

2014

Journal of electromagnetic engineering and science

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In this paper, we compare the quality of images reconstructed by a conventional delayed-sum (DS) algorithm and radiation pattern-based DS algorithm. In order to evaluate the quality of images, we apply the target-to-clutter ratio (TCR), which is commonly used in synthetic aperture radar (SAR) image assessment. The radiation pattern-based DS algorithm enhances the TCR of the image by focusing the target signals and preventing contamination of the radar scene. We first consider synthetic data obtained through GprMax2D/3D, a finite-difference time-domain (FDTD) forward solver. Experimental data of a 2-GHz bandwidth stepped-frequency signal are collected using a vector network analyzer (VNA) in an anechoic chamber setup. The radiation pattern-based DS algorithm shows a 6.7-dB higher TCR compared to the conventional DS algorithm. This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/ by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. ⓒ

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“…There are various methods of mitigating such wall clutter [2][3][4]. In this paper, we adopt the subspace projection method.…”

Section: Wall Clutter Mitigationmentioning

confidence: 99%

“…There have been many studies on TWRI. Some have focused on TWRI system architecture [1], while others have investigated signal processing issues related to TWRI [2][3][4]. To make the system more complete, however, suitable reconstruction of the radar scene is indispensable.…”

Section: Introductionmentioning

confidence: 99%

Target-to-Clutter Ratio Enhancement of Images in Through-the-Wall Radar Using a Radiation Pattern-Based Delayed-Sum Algorithm

Lim¹,

Nam²

2014

Journal of electromagnetic engineering and science

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“…In [4], the properties of wall can be calculated by the insertion transfer function based on Green function, which estimates and images the position of hidden target accurately according to the propagation regulars of electromagnetic wave. In [7], the thickness and dielectric constant are estimated by filtering algorithms and used to image the hidden targets. By the aid of focus levels, the best focused radar image is picked out as the result of imaging.…”

Section: Introductionmentioning

confidence: 99%

Time-division MIMO through-the-wall radar imaging behind multiple walls

Wang

Cui

et al. 2015

2015 IEEE Radar Conference (RadarCon)

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This paper considers the imaging problem of a target hiding behind multiple walls with known thicknesses and dielectric constants using time-division multiple-input multipleoutput (MIMO) through-the-wall radar (TWR). We propose a novel back-projection-based algorithm. Specifically, we develop the signal model of one target hiding behind two parameters known walls for time-division MIMO TWR at first; secondly, we calculate the pixel values by back-projection-based algorithm where the focus delay can be computed applying Fermat theory and Snell's law to obtain a high quality image. Finally, we evaluate and prove the validation the proposed algorithm via several simulation results.

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“…Each iteration will add absent walls or cut out extra walls so as to be closer to the true layout of the building, comparing with the pre-iteration process. Then the positions of the wall-wall-floor trihedrals will be more accurate after compensation of the wall parameters [13]. To improve the computation efficiency of the iterative reconstruction method, prevent manual intervention during the reconstruction process and realize online computation, an effective building interior layout auto-reconstruction method need to be investigated.…”

Section: Introductionmentioning

confidence: 99%

Building interior layout reconstruction from through-the-wall radar image using MST-based method

Chen

Jin

et al. 2014

EURASIP J. Adv. Signal Process.

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In order to reconstruct the building interior layout from the through-the-wall radar image, this paper proposes a method based on minimum spanning tree (MST) which comes from the graph theory. The building layout graph (BLG) model is firstly established using the wall-wall-floor trihedrals inside the building. The vertex set and the edge set including the weight between any two nodes of the graph are defined afterwards. Then, the MST-based method is used to reconstruct the building interior layout. We have also improved the traditional method by applying the MST model with restricted conditions to solve the reconstruction problem when there exist interference targets in a building. The anechoic chamber measurements are carried out to demonstrate the suitability and efficacy of the MST-based method.

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Image-Domain Estimation of Wall Parameters for Autofocusing of Through-the-Wall SAR Imagery

Cited by 98 publications

References 24 publications

Target-to-Clutter Ratio Enhancement of Images in Through-the-Wall Radar Using a Radiation Pattern-Based Delayed-Sum Algorithm

Target-to-Clutter Ratio Enhancement of Images in Through-the-Wall Radar Using a Radiation Pattern-Based Delayed-Sum Algorithm

Time-division MIMO through-the-wall radar imaging behind multiple walls

Building interior layout reconstruction from through-the-wall radar image using MST-based method

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