On Input Formats for Radar Micro-Doppler Signature Processing by Convolutional Neural Networks

arXiv:2404.08291v1 Announce Type: new
Abstract: Convolutional neural networks have often been proposed for processing radar Micro-Doppler signatures, most commonly with the goal of classifying the signals. The majority of works tend to disregard phase information from the complex time-frequency representation. Here, the utility of the phase information, as well as the optimal format of the Doppler-time input for a convolutional neural network, is analysed. It is found that the performance achieved by convolutional neural network classifiers is heavily influenced by …

abstract arxiv convolutional neural networks cs.cv information micro networks neural networks processing radar representation type utility