Slocalization: Sub-{\mu}W Ultra Wideband Backscatter Localization

TL;DR

Slocalization is a low-power ultra wideband backscatter system that achieves high-accuracy indoor localization by long-term integration of signals, suitable for energy-harvesting tags and complex environments.

Contribution

The paper introduces Slocalization, a novel sub-microwatt UWB backscatter localization system that enables high-precision indoor localization with minimal power and cost.

Findings

Achieves 30 cm median 3D localization error.

Recovers UWB backscatter signals in under 15 minutes.

Operates effectively over 30 meters with energy harvesting.

Abstract

Ultra wideband technology has shown great promise for providing high-quality location estimation, even in complex indoor multipath environments, but existing ultra wideband systems require tens to hundreds of milliwatts during operation. Backscatter communication has demonstrated the viability of astonishingly low-power tags, but has thus far been restricted to narrowband systems with low localization resolution. The challenge to combining these complimentary technologies is that they share a compounding limitation, constrained transmit power. Regulations limit ultra wideband transmissions to just -41.3 dBm/MHz, and a backscatter device can only reflect the power it receives. The solution is long-term integration of this limited power, lifting the initially imperceptible signal out of the noise. This integration only works while the target is stationary. However, stationary describes the vast majority of objects, especially lost ones. With this insight, we design Slocalization, a sub-microwatt, decimeter-accurate localization system that opens a new tradeoff space in localization systems and realizes an energy, size, and cost point that invites the localization of every thing. To evaluate this concept, we implement an energy-harvesting Slocalization tag and find that Slocalization can recover ultra wideband backscatter in under fifteen minutes across thirty meters of space and localize tags with a mean 3D Euclidean error of only 30 cm.