D-SLATS: Distributed Simultaneous Localization and Time Synchronization

TL;DR

D-SLATS is a distributed framework that jointly addresses time synchronization and localization in IoT networks using three algorithms, achieving high accuracy without centralized control.

Contribution

It introduces a novel distributed approach combining EKF and optimization techniques for joint time and location estimation in IoT devices.

Findings

Achieves up to 3 microseconds time synchronization accuracy.

Attains 30 cm localization error.

Validated on custom UWB testbed and quadrotor.

Abstract

Through the last decade, we have witnessed a surge of Internet of Things (IoT) devices, and with that a greater need to choreograph their actions across both time and space. Although these two problems, namely time synchronization and localization, share many aspects in common, they are traditionally treated separately or combined on centralized approaches that results in an ineffcient use of resources, or in solutions that are not scalable in terms of the number of IoT devices. Therefore, we propose D-SLATS, a framework comprised of three different and independent algorithms to jointly solve time synchronization and localization problems in a distributed fashion. The First two algorithms are based mainly on the distributed Extended Kalman Filter (EKF) whereas the third one uses optimization techniques. No fusion center is required, and the devices only communicate with their neighbors. The proposed methods are evaluated on custom Ultra-Wideband communication Testbed and a quadrotor, representing a network of both static and mobile nodes. Our algorithms achieve up to three microseconds time synchronization accuracy and 30 cm localization error.