IFNet: Deep Imaging and Focusing for Handheld SAR with Millimeter-wave Signals

arXiv:2405.02023v1 Announce Type: new
Abstract: Recent advancements have showcased the potential of handheld millimeter-wave (mmWave) imaging, which applies synthetic aperture radar (SAR) principles in portable settings. However, existing studies addressing handheld motion errors either rely on costly tracking devices or employ simplified imaging models, leading to impractical deployment or limited performance. In this paper, we present IFNet, a novel deep unfolding network that combines the strengths of signal processing models and deep neural networks to achieve robust imaging and focusing …

abstract arxiv cs.cv deployment devices errors however imaging radar simplified studies synthetic synthetic aperture radar tracking type