MetaRadar: Indoor Localization by Reconfigurable Metamaterials

TL;DR

MetaRadar leverages reconfigurable metamaterials to dynamically alter radio reflections, significantly enhancing indoor localization accuracy from decimeter to centimeter levels by differentiating RSS values at adjacent locations.

Contribution

The paper introduces MetaRadar, a novel system using reconfigurable metamaterials to improve RSS-based indoor localization accuracy through dynamic radio environment manipulation.

Findings

Achieved centimeter-level localization accuracy.

Demonstrated effective radio map prediction with compressive construction.

Significantly outperformed traditional RSS-based systems.

Abstract

Indoor localization has drawn much attention owing to its potential for supporting location based services. Among various indoor localization techniques, the received signal strength (RSS) based technique is widely researched. However, in conventional RSS based systems where the radio environment is unconfigurable, adjacent locations may have similar RSS values, which limits the localization precision. In this paper, we present MetaRadar, which explores reconfigurable radio reflection with a surface/plane made of metamaterial units for multi-user localization. By changing the reflectivity of metamaterial, MetaRadar modifies the radio channels at different locations, and improves localization accuracy by making RSS values at adjacent locations have significant differences. However, in MetaRadar, it is challenging to build radio maps for all the radio environments generated by metamaterial units and select suitable maps from all the possible maps to realize a high accuracy localization. To tackle this challenge, we propose a compressive construction technique which can predict all the possible radio maps, and propose a configuration optimization algorithm to select favorable metamaterial reflectivities and the corresponding radio maps. The experimental results show a significant improvement from a decimeter-level localization error in the traditional RSS-based systems to a centimeter-level one in MetaRadar.