RSL-Net: Localising in Satellite Images From a Radar on the Ground
This addresses vehicle localization for autonomous systems in all-weather conditions, representing a novel approach rather than an incremental improvement.
The paper tackles the problem of localizing a ground vehicle in satellite images using FMCW radar, achieving infrastructure-free localization without needing a radar-based map by leveraging readily available overhead imagery.
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.