Radar Fields: An Extension of Radiance Fields to SAR

TL;DR

This paper introduces 'radar fields', extending the concept of radiance fields to synthetic aperture radar images, enabling 3D surface modeling from radar data and opening possibilities for hybrid optical and radar imaging methods.

Contribution

It demonstrates the feasibility of applying radiance field techniques to SAR images, creating the first 'radar fields' and enabling surface modeling solely from radar data.

Findings

First implementation of radiance fields for SAR images

Surface models learned from radar images with similar complexity to optical methods

Potential for hybrid optical and radar imaging techniques

Abstract

Radiance fields have been a major breakthrough in the field of inverse rendering, novel view synthesis and 3D modeling of complex scenes from multi-view image collections. Since their introduction, it was shown that they could be extended to other modalities such as LiDAR, radio frequencies, X-ray or ultrasound. In this paper, we show that, despite the important difference between optical and synthetic aperture radar (SAR) image formation models, it is possible to extend radiance fields to radar images thus presenting the first "radar fields". This allows us to learn surface models using only collections of radar images, similar to how regular radiance fields are learned and with the same computational complexity on average. Thanks to similarities in how both fields are defined, this work also shows a potential for hybrid methods combining both optical and SAR images.