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- W4293094857 abstract "With the development of autonomous driving and intelligent transportation system, the outline size detection of a vehicle has been very critical in the field of road traffic. In our paper, we propose a vehicle width detection based on millimeter-wave frequency-modulated continuous wave radar for autonomous and assisted driving. First, the three-dimensional fast Fourier transform is performed on radar echo signals to get the range-velocity-angle (RVA) spectrum. Then, Order Statistic constant false alarm rate (OS-CFAR) is employed to obtain the information of vehicle scatters. To improve the angular resolution, the root multiple signal classification method is used. Finally, to improve measurement accuracy and reduce the complexity in training effectively, we propose a random forest method based on important features selection so that the width of vehicles can be calculated more precisely. Numerical results derived from real-world datasets show that the proposed calculation scheme of vehicle width achieves good accuracy." @default.
- W4293094857 created "2022-08-26" @default.
- W4293094857 creator A5010313255 @default.
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- W4293094857 date "2022-06-01" @default.
- W4293094857 modified "2023-09-26" @default.
- W4293094857 title "Vehicle Width Detection Based on Millimeter-Wave LFMCW Radar for Autonomous Driving" @default.
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- W4293094857 doi "https://doi.org/10.1109/vtc2022-spring54318.2022.9860700" @default.
- W4293094857 hasPublicationYear "2022" @default.
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