Experimental Results of a 3-D Millimeter-Wave Compressive Reflector Antenna Imaging System

Zhang, Weite; Molaei, Ali; Heredia-Juesas, Juan; Tirado, Luis; Graham, Katherine; Bisulco, Anthony; Gómez‐Sousa, Hipólito; Martínez-Lorenzo, José Ángel

doi:10.1109/lawp.2018.2875628

Cited by 10 publications

(5 citation statements)

References 29 publications

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“…1,2 Due to the special curved surface, the accuracy of the surface is required to reach 0.1 mm even higher when operating in the millimeter wave band. 3 The reflectarray has the advantages of small size, light weight, and high gain. The design challenge of the traditional microstrip reflectarray is the problem of narrow bandwidth.…”

Section: Introductionmentioning

confidence: 99%

Wideband 3D‐printed dielectric reflectarray in Ka‐band

Liao

Xing

et al. 2022

Micro & Optical Tech Letters

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An ultra‐wideband 3D‐printed dielectric reflectarray antenna (DRA) is proposed in this letter. The dielectric reflectarray unit (DRU) adopts the photosensitive resin therm1220, which dielectric constant of 3.97 is conducive to improving the bandwidth. Through adjusting the size of the DRU, the reflection phase can be adjusted. The dielectric reflectarray is 23 × 23 element which printed by stereo lithography apparatus (SLA) and is realized by installing a metal plate with four resin screws. The measured of the gain covers 25.8–28.9 dBi from 27.5 to 38 GHz. And the 3‐dB gain bandwidth of measured is 32.1%. The measured aperture efficiency is basically above 30% from 28 to 35 GHz. The maximum gain is 28.1 dBi at 30 GHz, and the aperture efficiency is 39% during measurement. The 3 dB beam width of the E‐plane and H‐plane are both about 5.4° in Ka‐band. A good agreement can be observed between measurement and simulation.

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Section: Introductionmentioning

confidence: 99%

Wideband 3D‐printed dielectric reflectarray in Ka‐band

Liao

Xing

et al. 2022

Micro & Optical Tech Letters

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“…Moreover, the weight of the product is large, and it is inconvenient to transport and install 1–2 . The surface accuracy of the millimeter wave antenna reflector is required to reach 0.1 mm or even higher 3 . The current reflector manufacturing method also includes the reflective panel fabrication based on the precision processing of the epoxy resin matrix surface and then silver spraying.…”

Section: Introductionmentioning

confidence: 99%

“…[1][2] The surface accuracy of the millimeter wave antenna reflector is required to reach 0.1 mm or even higher. 3 The current reflector manufacturing method also includes the reflective panel fabrication based on the precision processing of the epoxy resin matrix surface and then silver spraying. This method has a lot of procedures, requires large-scale processing equipment, and is costly and time-consuming.…”

Section: Introductionmentioning

confidence: 99%

3D ‐printed reflector antenna and metallization in Ka‐band

Xing

Liao

et al. 2022

Int J RF Mic Comp-Aid Eng

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A novel high precision and lightweight reflector antenna is proposed. The fabrication process of the reflector adopted Stereo Lithography Apparatus (SLA) printed and metallization. The proposed SLA Reflector (SLAR) antenna structure adopts three‐dimensional‐printed, which can design complex geometric shapes flexibly and rapid prototyping. That is a good substitute for the traditional method of millimeter wave reflector processing. In order to realize radio frequency (RF) characteristics perfectly, the metallization process of photosensitive resin was elaborated, which realized by first electroless nickel plating, then copper electroplating, and finally chromium electroplating on the protective layer. For verification, the designed reflector antenna was manufactured and measured. The reflectivity of SLAR was measured well by the bow method, which validates excellent fabrication accuracy and reliability. The gain and pattern were measured in the anechoic chamber. The results show that the proposed reflector antenna achieves the gain of 25 dBi and the 3 dB gain bandwidth of 43% over the full Ka‐band. A good agreement can be observed between measurement and simulation.

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“…As a result, mmW radar modalities have been widely used in places where security is of utmost importance. Various image processing techniques have been demonstrated on mmW images such as compressive sensing [13], [14], super-resolution [15], [16], denoising and image enhancement [17], [18]. Classification techniques on such images have been previously explored [19], [20], although the literature on these techniques is still scarce.…”

Section: Introductionmentioning

confidence: 99%

Coded-Aperture Computational Millimeter-Wave Image Classifier Using Convolutional Neural Network

et al. 2021

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A millimeter-wave (mmW) classifier system applied to images synthesized from a codedaperture based computational imaging (CI) radar is presented. A developed physical model of a CI system is used to generate the image dataset for the classification algorithm. A convolutional neural network (CNN) is integrated with the physical model and trained using the dataset comprising of synthesized mmW images obtained directly from the developed CI physical model. A k-fold cross validation technique is applied during the training process to validate the classification model. The coded-aperture CI concept enables image reconstruction from a significantly reduced number of back-scattered measurements by facilitating physical layer compression. This physical layer compression can substantially simplify the data acquisition layer of imaging radars, which is realized using only two channels in this article. The integration of the classification algorithm with the CI numerical model is particularly important in enabling the training step to be carried out using relevant system metrics and without the necessity for experimental data. Leveraging the CI numerical model generated data, training step for the classification algorithm is achieved in real-time while also confirming that the numerically trained CI classifier offers high accuracy with both simulated and experimental data. The classifier integrated physical model also enables performance analysis of the classification algorithm to be carried out as a function of key system metrics such as signal-to-noise (SNR) level, ensuring a complete understanding of the classification accuracy under different operating conditions. The trained CI system is tested with synthesized mmW images from the physical model and a classification accuracy of 89% is achieved. The proposed model is also verified using experimental data validating the fidelity of the developed CI integrated classifier system. A classification latency of 3.8 ms per frame is achieved, paving the way for real-time automated threat detection (ATD) for security-screening applications.INDEX TERMS Millimetre-wave, imaging radars, computational imaging, neural networks, image classification, coded-aperture.

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Experimental Results of a 3-D Millimeter-Wave Compressive Reflector Antenna Imaging System

Cited by 10 publications

References 29 publications

Wideband 3D‐printed dielectric reflectarray in Ka‐band

Wideband 3D‐printed dielectric reflectarray in Ka‐band

3D ‐printed reflector antenna and metallization in Ka‐band

Coded-Aperture Computational Millimeter-Wave Image Classifier Using Convolutional Neural Network

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