Congratulations to Simon on this achievemment!

Near-field 3D SAR imaging with no constraints on motion using physics-informed deep learning

Simon’s research focuses on Synthetic Aperture Radar (SAR), a technique that exploits motion to achieve high-resolution radar imaging without requiring large antenna arrays. However, traditional SAR methods rely on restrictive motion assumptions that limit their use in emerging applications such as autonomous navigation and drone-based sensing. Simon will address this gap by developing a physics-informed machine learning (PIML) framework for 3D imaging under arbitrary motion, which will be validated through real-world drone-based radar experiments.