Wide-bandwidth, wide-beamwidth, high-resolution, millimeter-wave imaging for concealed weapon detection

Sheen, David M.; Fernandes, Justin L.; Tedeschi, Jonathan R.; McMakin, Douglas L.; Jones, Anthony M.; Lechelt, Wayne M.; Severtsen, Ronald H.

doi:10.1117/12.2016132

Cited by 58 publications

(30 citation statements)

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“…Examples of the excellent resolution and fidelity that may be obtained using these imaging techniques have been previously shown by the author and a few important results are summarized here [8,9]. A 10-40 GHz planar imaging result for an unclothed mannequin is shown in Figure 1.…”

Section: Introductionmentioning

confidence: 66%

Noise analysis for near-field 3D FM-CW radar imaging systems

Sheen

2015

SPIE Proceedings

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Near field radar imaging systems are used for demanding security applications including concealed weapon detection in airports and other high-security venues. Despite the near-field operation, phase noise and thermal noise can limit performance in several ways. Practical imaging systems can employ arrays with low gain antennas and relatively large signal distribution networks that have substantial losses which limit transmit power and increase the effective noise figure of the receiver chain, resulting in substantial thermal noise. Phase noise can also limit system performance. The signal coupled from transmitter to receiver is much larger than expected target signals. Phase noise from this coupled signal can set the system noise floor if the oscillator is too noisy. Frequency modulated continuous wave (FM-CW) radar transceivers used in short range systems are relatively immune to the effects of the coupled phase noise due to range correlation effects. This effect can reduce the phase-noise floor such that it is below the thermal noise floor for moderate performance oscillators. Phase noise is also manifested in the range response around bright targets, and can cause smaller targets to be obscured. Noise in synthetic aperture imaging systems is mitigated by the processing gain of the system. In this paper, the effects of thermal noise, phase noise, and processing gain are analyzed in the context of a near field 3-D FM-CW imaging radar as might be used for concealed weapon detection. In addition to traditional frequency domain analysis, a time-domain simulation is employed to graphically demonstrate the effect of these noise sources on a fast-chirping FM-CW system.

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Section: Introductionmentioning

confidence: 66%

Noise analysis for near-field 3D FM-CW radar imaging systems

Sheen

2015

SPIE Proceedings

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“…However, passive imagers have undesirable shortages of low resolution, faint signals, and large noise, thus they usually yield blurry images. Unlike passive imaging sensors, an active imager can achieve a high resolution, high quality, clear imaging results [2][3][4]9], and is widely adopted by modern high-security facilities. In general, an MMW 3D active imager is realized by a synthetic aperture processing over a wide frequency and spatial sampling, followed by the reconstruction of the reflectivity distribution over the target spatial domain, which finally generates MMW images.…”

Section: Introductionmentioning

confidence: 99%

Towards Robust Human Millimeter Wave Imaging Inspection System in Real Time With Deep Learning

Liu¹,

Yang²,

Sun³

2018

PIER

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With the ever-growing requirements of human security check in public, near-field millimeter wave (MMW) imaging techniques have been developing rapidly in recent years. Due to the lack of MMW images, low resolution and indistinguishable texture in most MMW images, it is still a great challenge to do high performance object detection task on MMW images. In this paper, we propose a novel framework to automatically detect concealed weapons and potential dangerous objects based on a single human millimeter wave image, in which a deep convolutional neural network (CNN) is presented to simultaneously extract features, detect suspicious objects, and give the confidence score. Unlike traditional optical image level solutions, we comprehensively analyze the original MMW data for object representation, incorporate domain-specific knowledge to design and train our network. Moreover, combined with the modern focal loss theory, we devise an effective loss function elaborately to optimize our model. Experimental results on both our dataset and real world data show the effectiveness and improvement of our method compared with the state-of-the-arts.

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“…The Pacific Northwest National Laboratory (PNNL) has developed imaging techniques and systems applied to many of these applications [3][4][5][6][7][8][9]. In particular, PNNL developed and licensed the cylindrical mm-wave technology that is now widely deployed in airports in the United States and around the world.…”

Section: Introductionmentioning

confidence: 99%

Reconstruction techniques for sparse multistatic linear array microwave imaging

Sheen

Hall

2014

SPIE Proceedings

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Sequentially-switched linear arrays are an enabling technology for a number of near-field microwave imaging applications. Electronically sequencing along the array axis followed by mechanical scanning along an orthogonal axis allows dense sampling of a two-dimensional aperture in near real-time. The Pacific Northwest National Laboratory (PNNL) has developed this technology for several applications including concealed weapon detection, groundpenetrating radar, and non-destructive inspection and evaluation. These techniques form three-dimensional images by scanning a diverging beam swept frequency transceiver over a two-dimensional aperture and mathematically focusing or reconstructing the data into three-dimensional images. Recently, a sparse multi-static array technology has been developed that reduces the number of antennas required to densely sample the linear array axis of the spatial aperture. This allows a significant reduction in cost and complexity of the linear-array-based imaging system. The sparse array has been specifically designed to be compatible with Fourier-Transform-based image reconstruction techniques; however, there are limitations to the use of these techniques, especially for extreme near-field operation. In the extreme near-field of the array, back-projection techniques have been developed that account for the exact location of each transmitter and receiver in the linear array and the 3-D image location. In this paper, the sparse array technique will be described along with associated Fourier-Transform-based and back-projection-based image reconstruction algorithms. Simulated imaging results are presented that show the effectiveness of the sparse array technique along with the merits and weaknesses of each image reconstruction approach.

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Wide-bandwidth, wide-beamwidth, high-resolution, millimeter-wave imaging for concealed weapon detection

Cited by 58 publications

References 0 publications

Noise analysis for near-field 3D FM-CW radar imaging systems

Noise analysis for near-field 3D FM-CW radar imaging systems

Towards Robust Human Millimeter Wave Imaging Inspection System in Real Time With Deep Learning

Reconstruction techniques for sparse multistatic linear array microwave imaging

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