DeepHybrid: Deep Learning on Automotive Radar Spectra and Reflections for Object Classification
Adriana-Eliza Cozma,
Lisa Morgan,
Martin Stolz
et al.
Abstract:Automated vehicles need to detect and classify objects and traffic participants accurately. Reliable object classification using automotive radar sensors has proved to be challenging. We propose a method that combines classical radar signal processing and Deep Learning algorithms. The range-azimuth information on the radar reflection level is used to extract a sparse region of interest from the range-Doppler spectrum. This is used as input to a neural network (NN) that classifies different types of stationary … Show more
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