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Zhu, S. (author), Yarovoy, Alexander (author), Fioranelli, F. (author)The problem of instantaneous ego-motion estimation with mm-wave automotive radar is studied. DeepEgo, a deep learning-based method, is proposed for achieving robust and accurate ego-motion estimation. A hybrid approach that uses neural networks to extract complex features from input point clouds and applies weighted least squares (WLS) for...journal article 2023
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Yuan, S. (author), Zhu, S. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)The problem of estimating the 3D ego-motion velocity using multi-channel FMCW radar sensors has been studied. For the first time, the problem of ego-motion estimation is treated using radar raw signals. A robust algorithm using multi-channel FMCW radar sensors to instantly determine the complete 3D motion state of the ego-vehicle (i.e.,...journal article 2023
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Zhu, S. (author), Fioranelli, F. (author), Yarovoy, Alexander (author)The problem of 2D instantaneous ego-motion estimation for vehicles equipped with automotive radars is studied. To leverage multi-dimensional radar point clouds and exploit point features automatically, without human engineering, a novel approach is proposed that transforms ego-motion estimation into a weighted least squares (wLSQ) problem using...conference paper 2023
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Zhu, S. (author), Guendel, Ronny (author), Yarovoy, Alexander (author), Fioranelli, F. (author)Unconstrained human activities recognition with a radar network is considered. A hybrid classifier combining both convolutional neural networks (CNNs) and recurrent neural networks (RNNs) for spatial–temporal pattern extraction is proposed. The 2-D CNNs (2D-CNNs) are first applied to the radar data to perform spatial feature extraction on the...journal article 2022