A Simple Strategy to Detect Changes in Through the Wall Imaging

Soldovieri, Francesco; Solimene, Raffaele; Pierri, Rocco

doi:10.2528/pierm09030902

Cited by 40 publications

(27 citation statements)

References 19 publications

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“…Examples of applications include earthquake and fire rescue operations, police search operations, homeland security, and military applications as reported in several work in the literature [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19]. The reported results in [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17] were based on permittivity reconstruction of hidden objects behind a wall, while works in [18][19][20] were focused on the shape reconstruction of hidden objects.…”

Section: Introductionmentioning

confidence: 99%

The Level Set Shape Reconstruction Algorithm Applied to 2d Pec Targets Hidden Behind a Wall

Hajihashemi¹,

El-Shenawee²

2010

PIER B

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Abstract-The level set algorithm is extended to handle the reconstruction of the shape and location of objects hidden behind a dielectric wall. The Green's function of stratified media is used to modify the method of moments and the surface integral equation forward solver. Due to the oscillatory nature of the Sommerfeld integrals, the stationary phase approximation is implemented here to achieve fast and accurate reconstruction results, especially when the targets are located adequately far from the wall. Transverse Magnetic (TM) plane waves are employed for excitation with limited view for transmitting and receiving the waves in the far field at one side of the wall. The results show the capability of the level set method for retrieving the shape and location of multiple 2D PEC objects of arbitrary shapes even when there are located at a small distance from the wall. To reduce the computational expenses of the algorithm in the case of multiple hidden objects, the MPI parallelization technique is implemented leading to a reduction in the CPU time from hours on a single processor to few minutes using 128 processors on the NCSA Supercomputer Center.

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Section: Introductionmentioning

confidence: 99%

The Level Set Shape Reconstruction Algorithm Applied to 2d Pec Targets Hidden Behind a Wall

Hajihashemi¹,

El-Shenawee²

2010

PIER B

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“…In order to verify experimentally the principle of the method proposed in [15], we turn to consider two different situations where a static scatter is present in the scene whereas the mannequin is located at two different positions. The static scatterer is a metallic coat hanger 1.7 m in height whose main part is a 5 cm diameter cylinder 1.5 m in height.…”

Section: Reconstruction Resultsmentioning

confidence: 99%

“…In this case, a simple procedure able to counteract the clutter due to static scatterers could be employed. For example, a procedure based on the incoherent difference between two reconstructions obtained at two different instants of time in principle allows to discern a moving target from static objects [15].…”

Section: Reconstruction Resultsmentioning

confidence: 99%

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3d Sliced Tomographic Inverse Scattering Experimental Results

Solimene¹,

Brancaccio²,

Napoli³

et al. 2010

PIER

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Abstract-The problem of imaging three-dimensional strong scatterers by means of a two-dimensional sliced tomographic reconstruction algorithm is dealt with. In particular, the focus of the paper is on the experimental validation of the involved inversion algorithm thanks to measurements collected in a controlled environment. A simple strategy exploiting reconstructions obtained at different time instants in order to detect slowly moving scatterers is also experimentally validated.

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“…Doppler signatures or change detection techniques [6]- [8] cannot be applied since the targets of interest and clutter are both of the same stationary nature. Stationary target detection is typically performed subsequent to image formation [2].…”

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confidence: 99%

Pattern Matching for Building Feature Extraction

Lagunas

Amin

Ahmad

et al. 2014

IEEE Geosci. Remote Sensing Lett.

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Abstract-We address the problem of detecting building dominant scatterers using a reduced number of measurements with applications to through-the-wall radar (TWR) and urban sensing. We consider oblique illumination, which specially enhances the radar returns from the corners formed by the orthogonal intersection of two walls. This letter uses a novel type of image descriptor, named correlogram, which encodes information about spatial correlation of complex amplitudes of each TWR image pixel. The proposed technique compares the known correlogram of the scattering response of an isolated canonical corner reflector with the correlogram of the received radar signal. The feature-based nature of the proposed detector enables corner separation from other indoor scatterers, such as humans.Index Terms-Building dominant scatterers, pattern matching, through-the-wall radar imaging (TWRI).

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A Simple Strategy to Detect Changes in Through the Wall Imaging

Cited by 40 publications

References 19 publications

The Level Set Shape Reconstruction Algorithm Applied to 2d Pec Targets Hidden Behind a Wall

The Level Set Shape Reconstruction Algorithm Applied to 2d Pec Targets Hidden Behind a Wall

3d Sliced Tomographic Inverse Scattering Experimental Results

Pattern Matching for Building Feature Extraction

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