Vehicle Recognition Based on Carrier-Free UWB Radars Using Contrastive Multi-View Learning

Zhu, Yuying; Zhang, Shuning; Zhu, Yuying

doi:10.1109/lmwc.2022.3216048

IEEE Microw. Wireless Tech. Lett.

2023

DOI: 10.1109/lmwc.2022.3216048

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Vehicle Recognition Based on Carrier-Free UWB Radars Using Contrastive Multi-View Learning

Yuying Zhu

Shuning Zhang

Yuying Zhu

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Cited by 3 publications

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A review on multi-view learning

Yu,

Dong,

et al. 2024

Front. Comput. Sci.

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Multi-view learning is an emerging field that aims to enhance learning performance by leveraging multiple views or sources of data across various domains. By integrating information from diverse perspectives, multi-view learning methods effectively enhance accuracy, robustness, and generalization capabilities. The existing research on multi-view learning can be broadly categorized into four groups in the survey based on the tasks it encompasses, namely multi-view classification approaches, multi-view semi-supervised classification approaches, multi-view clustering approaches, and multi-view semi-supervised clustering approaches. Despite its potential advantages, multi-view learning poses several challenges, including view inconsistency, view complementarity, optimal view fusion, the curse of dimensionality, scalability, limited labels, and generalization across domains. Nevertheless, these challenges have not discouraged researchers from exploring the potential of multiview learning. It continues to be an active and promising research area, capable of effectively addressing complex real-world problems.

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A review on multi-view learning

Yu,

Dong,

et al. 2024

Front. Comput. Sci.

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An Anti-Jamming Method of UWB Ranging Sensor Based on Equivalent Sampling and Coupled Chaotic Oscillator

Wang

Zhang

Chen

et al. 2023

IEEE Microw. Wireless Tech. Lett.

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A compact high gain UWB planar monopole antenna using circular slots

Mishra,

Patnaik,

Panda

et al. 2024

Serb J Electr Eng

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In this manuscript, the design of a compact-size circular patch Ultra- Wideband (UWB) antenna with enhanced fractional bandwidth (BW), peak realized gain (PRG), and proper impedance matching is presented. The modified antenna has three circular slots etched from the circular path (top), fed by a 50? microstrip feed line. These circular slots play a significant role in improving the impedance bandwidth. Additionally, the partial ground plane with a slot integrated with a rectangular stub is used in order to achieve a bandwidth for an operating range of 3.25 GHz - 27 GHz. The proposed antenna is designed, fabricated, and tested in the laboratory in order to validate with simulation data. The designed antenna size is 25 mm ? 20 mm ? 0.508 mm. The experimental value of 10 dB return loss absolute/fractional BW of 23.75 GHz/157.08% at the center frequency, minimum/ maximum gain of 5.90/12.05 dBi, and maximum /minimum radiation efficiency of 85/97 % are achieved from the 3.25 GHz to 27 GHz frequency range. In addition, a comparison table is provided to prove the state-of-the-art of the antenna?s design. The proposed antenna is suitable for wireless services, radar, and satellite communication.

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Vehicle Recognition Based on Carrier-Free UWB Radars Using Contrastive Multi-View Learning

Cited by 3 publications

References 18 publications

A review on multi-view learning

A review on multi-view learning

An Anti-Jamming Method of UWB Ranging Sensor Based on Equivalent Sampling and Coupled Chaotic Oscillator

A compact high gain UWB planar monopole antenna using circular slots

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