RSL-Net: Localising in Satellite Images From a Radar on the Ground
Abstract
This paper is about localising a vehicle in an overhead image using FMCW radar mounted on a ground vehicle. FMCW radar offers extraordinary promise and efficacy for vehicle localisation. It is impervious to all weather types and lighting conditions. However the complexity of the interactions between millimetre radar wave and the physical environment makes it a challenging domain. Infrastructure-free large-scale radar-based localisation is in its infancy. Typically here a map is built and suitable techniques, compatible with the nature of sensor, are brought to bear. In this work we eschew the need for a radar-based map; instead we simply use an overhead image -- a resource readily available everywhere. This paper introduces a method that not only naturally deals with the complexity of the signal type but does so in the context of cross modal processing.
Keywords
Cite
@article{arxiv.2001.03233,
title = {RSL-Net: Localising in Satellite Images From a Radar on the Ground},
author = {Tim Y. Tang and Daniele De Martini and Dan Barnes and Paul Newman},
journal= {arXiv preprint arXiv:2001.03233},
year = {2020}
}
Comments
Accepted to IEEE Robotics and Automation Letters (RA-L)