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Angle-Equivariant Convolutional Neural Networks for Interference Mitigation in Automotive Radar
In automotive applications, frequency modulated continuous wave (FMCW) radar is an established technology to determine the distance, velocity and angle of objects in the vicinity of the vehicle.
End-to-End Training of Neural Networks for Automotive Radar Interference Mitigation
In this paper we propose a new method for training neural networks (NNs) for frequency modulated continuous wave (FMCW) radar mutual interference mitigation.
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