3D imaging system based on a MIMO approach at 360GHz for security screening

Nowok, Sandra; Herschel, Reinhold; Zimmermann, Rüdiger; Shoykhetbrod, Alex; Lang, Simon R.; Pohl, Nils

doi:10.1109/piers.2016.7734419

Cited by 4 publications

(3 citation statements)

References 3 publications

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“…Before doing so the signal is cropped regarding to determined edge position. Additionally, the signal is processed with a moving average filter causing a smoothing effect which was lost by neglecting the sinc in (5). As result, the image is compensated revealing further diffraction effects caused by the true surface roughness.…”

Section: ) Diffraction Compensation For Surface Monitoringmentioning

confidence: 99%

Diffraction From Metallic Objects in Radar Imaging—Theory, Simulation, and Experimental Verification

et al. 2022

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The paper describes the modelling of diffraction effects in radar imaging scans at and near sharp-edged metallic objects as the aperture dimension is close to the dimension of the object to be scanned. We evaluate the Fresnel-Kirchhoff integral within the process of radar imaging for an 1D synthetic aperture radar. The resulting compact imaging model describes the diffraction effects in a single convolution-based formula. This is the basis for the simulative analysis in which the derived model is compared to a numerical radar imaging model. Further, we test our derived diffraction model experimentally. It confirms the developed theory and opens up additional areas of application for diffraction effect impacted radar imaging. This might be: high precision cross-range measurement with micrometer accuracy; highly precise surface reconstruction unveiling surface uncertainties in the low double-digit micrometer range; and model-based radar image enhancement.INDEX TERMS Diffraction, millimeter wave radar, radar imaging, radar measurements, radar theory, synthetic aperture radar (SAR). This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. SCHLOSSER ET AL.: DIFFRACTION FROM METALLIC OBJECTS IN RADAR IMAGING -THEORY, SIMULATION AND EXPERIMENTAL VERIFICATION integrated on consumer electronic platforms to provide images based on radar scanning technology [5], [6] and [7].

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Section: ) Diffraction Compensation For Surface Monitoringmentioning

confidence: 99%

Diffraction From Metallic Objects in Radar Imaging—Theory, Simulation, and Experimental Verification

et al. 2022

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“…Active terahertz video surveillance is historically associated with such areas as radar and holography [39,41]. At present, in the field of active terahertz observation, it has been proposed to use the mechanical and digital beam formation [20,42,43], terahertz holography [44,45], time-of-flight terahertz tomography [46], synthesized apertures [47] to obtain information on the threedimensional surface of the object under study -49], coding apertures [50][51][52][53][54], frequency modulation of the signal [55], antennas from metamaterials [56], etc.…”

Section: Combining the Capabilities Of Thz And 3d Video: The History mentioning

confidence: 99%

Semantic Fusion and Joint Analysis of Terahertz and 3d Video Images by the Means of Object-Oriented Logic Programming

Morozov¹,

Sushkova²,

Polupanov³

et al. 2018

RENSIT

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The aim of the work is to create methods and software tools for the terahertz range intelligent video surveillance, that is, for automatic analysis of video images in the terahertz frequency range. Terahertz video surveillance provides unique prospects in the area of public safety; in particular, it allows you to remotely identify weapons and dangerous items hidden under clothing on the human body. However, such characteristics of terahertz video, as low resolution, low contrast, and low signal-to-noise ratio, lead to the need to develop new methods and approaches to automatic video analysis. To understand the terahertz video image, the operator of the industrial video surveillance system usually compares it with images in other frequency ranges (visible or infrared). The comparison of these images of different types helps the operator to interpret the colored and/ or one-color spots in the terahertz image in a proper way. In terms of automatic video analysis, this means that the context of the observed events and objects is taken into account, or in other words, a semantic fusion is implemented of the terahertz range video image with video images of other frequency ranges, e.g., near-infrared, visible, etc. The authors consider the semantic fusion of the video images as a critical component of the prospective terahertz intelligent video surveillance technology. A new method of the terahertz video surveillance based on the fusion of the terahertz video with 3D video is proposed. The means of the object-oriented logic programming developed for the semantic fusion of the terahertz and 3D video images are described. The developed method provides a real-time fusion of the terahertz video acquired using the THERZ-7A (Astrohn Technology Ltd) subterahertz scanning device (0.23-0.27 THz) and 3D video data acquired using the Kinect 2 (Microsoft Inc) time-of-flight sensor. The method and software tools for the semantic fusion of the terahertz and 3D video images are developed.

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“…Different approaches are also investigated in previous works. In [11], a system based on the combination of MIMO radar for DoA estimation on the azimuth angle and mechanical beam steering in the elevation angle is proposed. In [12], the 3-D-imaging is performed using a system composed of two orthogonal leaky wave antennas capable to perform steering of the main lobe through frequency scanning.…”

Section: Introductionmentioning

confidence: 99%

2-D MIMO Radar: A Method for Array Performance Assessment and Design of a Planar Antenna Array

Serio¹,

Hügler²,

Roos³

et al. 2020

IEEE Trans. Antennas Propagat.

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In this article, a method for the assessment of the performance and for the design of a 2-D-array for multiple input multiple output (2-D-MIMO) radar applications is presented. The proposed approach is based on the analysis of the ambiguity function associated with the array. Such analysis leads to the definition of an area in the 2-D-angular field-of-view of the radar, denoted as ambiguity-free region, characterized by a low probability to obtain ambiguities in direction of arrival estimation. Simulations of a basic 2-D-MIMO array are used to explain the proposed method, which is then employed as the main criterion for the optimization of a 2-D-MIMO sparse array composed of four transmitters and eight receivers. The optimization is performed through a genetic algorithm. The resulted element positions guarantee an ambiguity-free region span in the azimuth and elevation angles greater than 120 • and angular resolutions of 8 • and 5.9 • on the azimuth and elevation angles, respectively. The optimized positions are then used to realize a 2-D-MIMO sparse array that is integrated in a radar system operating at a center frequency of 76.5 GHz. Such an array is calibrated, and comparisons between the simulated and measured ambiguity functions show the effectiveness of the proposed method.

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3D imaging system based on a MIMO approach at 360GHz for security screening

Cited by 4 publications

References 3 publications

Diffraction From Metallic Objects in Radar Imaging—Theory, Simulation, and Experimental Verification

Diffraction From Metallic Objects in Radar Imaging—Theory, Simulation, and Experimental Verification

Semantic Fusion and Joint Analysis of Terahertz and 3d Video Images by the Means of Object-Oriented Logic Programming

2-D MIMO Radar: A Method for Array Performance Assessment and Design of a Planar Antenna Array

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