A Novel Micro-Doppler Coherence Loss for Deep Learning Radar Applications

arXiv:2404.15346v1 Announce Type: cross
Abstract: Deep learning techniques are subject to increasing adoption for a wide range of micro-Doppler applications, where predictions need to be made based on time-frequency signal representations. Most, if not all, of the reported applications focus on translating an existing deep learning framework to this new domain with no adjustment made to the objective function. This practice results in a missed opportunity to encourage the model to prioritize features that are particularly relevant for micro-Doppler applications. …

abstract adoption applications arxiv cs.cv cs.lg deep learning deep learning framework deep learning techniques eess.sp focus framework loss micro novel predictions radar signal type