Inverse Rendering of Near-Field mmWave MIMO Radar for Material Reconstruction

Nikolai Hofmann¹, Vanessa Wirth¹, Johanna Bräunig¹, Ingrid Ullmann¹, Martin Vossiek¹, Tim Weyrich^1,2, Marc Stamminger¹

¹ Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
² University College London

Abstract

Near-field multiple-input multiple-output (MIMO) radar systems allow for high-resolution spatial imaging by leveraging multiple antennas to transmit and receive signals across multiple perspectives. This capability is particularly advantageous in challenging environments, where optical imaging techniques struggle. We present a novel approach to inverse rendering for near-field MIMO radar systems, aimed at reconstructing material properties such as surface roughness, dielectric constants, and conductivity from radar and ground-truth mesh data, for example obtained from multi-view stereo. Drawing inspiration from physically based rendering techniques in computer graphics, we formalize an advanced inverse rendering algorithm that integrates electromagnetic wave propagation models directly into the optimization process. To avoid bias from conventional radar image reconstruction algorithms in the optimization process, we directly derive gradients from raw radar outputs, resulting in more accurate material characterization. We validate our approach through extensive experiments on both synthetic and real radar datasets, demonstrating its effectiveness in a multitude of scenarios.

Citation Style: Display Alpha ACM SIGGRAPH IEEEtran Publication

Inverse Rendering of Near-Field mmWave MIMO Radar for Material Reconstruction.
Nikolai Hofmann, Vanessa Wirth, Johanna Bräunig, Ingrid Ullmann, Martin Vossiek, Tim Weyrich, Marc Stamminger.
IEEE Journal of Microwaves (early access), 17 pages, February 2025..

Acknowledgments

This work was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – SFB 1483 – Project-ID 442419336, EmpkinS. The authors gratefully acknowledge the scientific support and HPC resources provided by the Erlangen National High Performance Computing Center (NHR@FAU) of the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) under the NHR Project b201dc. NHR is supported by Federal and Bavarian State Authorities. NHR@FAU Hardware was supported by the DFG – Project-ID 440719683. The authors would like to thank the Rohde & Schwarz GmbH & Co. KG (Munich, Germany) for providing the radar imaging device and technical support which made this work possible.