Design of Circular Polarized Antenna Using Gammadion Chiral Metamaterial as Linear-to-Circular Polarization Transformer

Kaur, Preet; Prajapati, Pravin R.

doi:10.2528/pierm20061806

Cited by 3 publications

(1 citation statement)

References 25 publications

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“…The model has an excellent recognition effect, and the model has good fault tolerance. Although the above studies have improved or improved the mainstream CNN and RNN models, sensor data and image data are different after all, and the transplantation of effective image processing algorithms to sensor data may fail [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Multimodal Sensor Motion Intention Recognition Based on Three‐Dimensional Convolutional Neural Network Algorithm

Wen

Wang

2021

Computational Intelligence and Neuroscience

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With the development of microelectronic technology and computer systems, the research of motion intention recognition based on multimodal sensors has attracted the attention of the academic community. Deep learning and other nonlinear neural network models have a wide range of applications in big data sets. We propose a motion intention recognition algorithm based on multimodal long-term and short-term spatiotemporal feature fusion. We divide the target data into multiple segments and use a three-dimensional convolutional neural network to extract the short-term spatiotemporal features. The three types of features of the same segment are fused together and input into the LSTM network for time-series modeling to further fuse the features to obtain multimodal long-term spatiotemporal features with higher discrimination. According to the lower limb movement pattern recognition model, the minimum number of muscles and EMG signal characteristics required to accurately recognize the movement state of the lower limbs are determined. This minimizes the redundant calculation cost of the model and ensures the real-time output of the system results.

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Section: Introductionmentioning

confidence: 99%

[Retracted] Multimodal Sensor Motion Intention Recognition Based on Three‐Dimensional Convolutional Neural Network Algorithm

Wen

Wang

2021

Computational Intelligence and Neuroscience

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Bilayer split-ring chiral metamaterial based reconfigurable antenna for polarization conversion

Kaur

Prajapati²

2021

Frequenz

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A bilayer split-ring chiral metamaterial converts the linearly polarized wave, into a nearly perfect left or right-handed circularly polarized wave. The proposed antenna is intended to operate at center frequency of 5.80 GHz with switchable polarization capability. The polarization re-configurability is achieved by electronically switching of two PIN-diode pairs, which are embedded into bilayer split-ring Chiral Metamaterial. The optimized length of rectangular patch is 16 mm and width is 12.1 mm. Two types of radiation characteristics offered by the proposed antenna; left hand circularly polarized in mode 1 and right hand circularly polarized in mode 2. Measured results show that its impedance bandwidth is 155 MHz from 5.70 to 5.855 GHz for both mode 1 and mode 2. The measured axial-ratio bandwidth is 100 MHz from 5.75 to 5.85 GHz for mode 1 and 110 MHz from 5.73 to 5.84 GHz for mode 2. Antenna has LHCP gain of 2.52 dBi and RHCP gain of −23 dBi in mode 1. RHCP gain of 2 dBi and polarization purity of about −20 dBi is obtained in mode 2. The proposed antenna has simple structure, low cost and it has potential application in field of wireless communication (i.e., WiMax, WLAN etc.).

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A circularly polarized folded reflectarray antenna using a polarization-sensitive linear-to-circular polarization converter

Liu

Wong

et al. 2022

Front. Phys.

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This work proposes a low-profile circularly polarized folded reflectarray antenna (CPFRA). Compared to traditional CPFRA that comprise the main reflectarray, a polarization grid (PG), and a linear-to-circular polarization (LP-CP) converter, the proposed CPFRA utilizes a polarization-sensitive LP-CP converter that plays the roles of both PG and LP-CP converter to minimize the CPFRA profile. One period of the polarization-sensitive LP-CP converter consists of an LP and a CP patch on the bottom and top layer of the substrates, respectively, which are connected by a metalized via. Due to its frequency-selective characteristic, the polarization-sensitive LP-CP surface can simultaneously reflect the x-polarized waves and transfer the received y-polarized waves into the CP state. A 1-bit unit cell at the bottom layer is adopted for polarization conversion and phase shift. A planar patch antenna is integrated as the primary feeding source. A high-gain circularly polarized folded reflectarray antenna at the X-band is designed, fabricated, and measured. Both simulated and measured results demonstrate the advantages of high gain and a lower profile of the proposed CPFRA compared to those in its traditional counterparts.

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Design of Circular Polarized Antenna Using Gammadion Chiral Metamaterial as Linear-to-Circular Polarization Transformer

Cited by 3 publications

References 25 publications

[Retracted] Multimodal Sensor Motion Intention Recognition Based on Three‐Dimensional Convolutional Neural Network Algorithm

[Retracted] Multimodal Sensor Motion Intention Recognition Based on Three‐Dimensional Convolutional Neural Network Algorithm

Bilayer split-ring chiral metamaterial based reconfigurable antenna for polarization conversion

A circularly polarized folded reflectarray antenna using a polarization-sensitive linear-to-circular polarization converter

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