Performance Analysis of Adaptive Cruise Control Using Frequency Modulated Continuous Wave Radar Under Rain Clutter

Shibly, Imam Hossain; Zaman, Md. Maniruz; Hossain, Md. Selim; Hasan, Mia Mohammad Shoaib

doi:10.1109/iccit60459.2023.10441169

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2024

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Cited by 3 publications

References 14 publications

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Performance Analysis of Highway Vehicle Tracking Using Different Object Trackers

Shanto,

Al Razi,

Hossain

et al. 2024

2024 IEEE International Conference on Power, Electrical, Electronics and Industrial Applications (PEEIACON)

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Performance Analysis of Highway Vehicle Tracking Using Different Object Trackers

Shanto,

Al Razi,

Hossain

et al. 2024

2024 IEEE International Conference on Power, Electrical, Electronics and Industrial Applications (PEEIACON)

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Advancements in Radar Technology for Enhanced Adaptive Cruise Control Systems

Zaman,

Shibly,

Hossain

et al. 2024

2024 IEEE International Conference on Power, Electrical, Electronics and Industrial Applications (PEEIACON)

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Anti-Rain Clutter Interference Method for Millimeter-Wave Radar Based on Convolutional Neural Network

Zhan,

Zhang,

Sun

et al. 2024

Remote Sensing

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Millimeter-wave radars are widely used in various environments due to their excellent detection capabilities. However, the detection performance in severe weather environments is still an important research challenge. In this paper, the propagation characteristics of millimeter-wave radar in a rainfall environment are thoroughly investigated, and the modeling of the millimeter-wave radar echo signal in a rainfall environment is completed. The effect of rainfall on radar detection performance is verified through experiments, and an anti-rain clutter interference method based on a convolutional neural network is proposed. The method combines image recognition and classification techniques to effectively distinguish target signals from rain clutter in radar echo signals based on feature differences. In addition, this paper compares the recognition results of the proposed method with VGGnet and Resnet. The experimental results show that the proposed convolutional neural network method significantly improves the target detection capability of the radar system in a rainfall environment, verifying the method’s effectiveness and accuracy. This study provides a new solution for the application of millimeter-wave radar in severe weather conditions.

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Performance Analysis of Adaptive Cruise Control Using Frequency Modulated Continuous Wave Radar Under Rain Clutter

Cited by 3 publications

References 14 publications

Performance Analysis of Highway Vehicle Tracking Using Different Object Trackers

Performance Analysis of Highway Vehicle Tracking Using Different Object Trackers

Advancements in Radar Technology for Enhanced Adaptive Cruise Control Systems

Anti-Rain Clutter Interference Method for Millimeter-Wave Radar Based on Convolutional Neural Network

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