Synchronization and Localization in Ad-Hoc ICAS Networks Using a Two-Stage Kuramoto Method

TL;DR

This paper presents a distributed, signal-agnostic synchronization and localization scheme for vehicular ICAS networks, addressing finite sampling effects to improve accuracy in peer-to-peer communication.

Contribution

It introduces a novel joint synchronization and localization method based on a two-stage Kuramoto approach, applicable to diverse ICAS signals and robust against sampling limitations.

Findings

Scheme achieves precise synchronization and localization in vehicular networks.

Method is robust to finite sampling frequency effects.

Applicable to a wide range of ICAS signals.

Abstract

To enable Integrated Communications and Sensing (ICAS) in a peer-to-peer vehicular network, precise synchronization in frequency and phase among the communicating entities is required. In addition, self-driving cars need accurate position estimates of the surrounding vehicles. In this work, we propose a joint, distributed synchronization and localization scheme for a network of communicating entities. Our proposed scheme is mostly signal-agnostic and therefore can be applied to a wide range of possible ICAS signals. We also mitigate the effect of finite sampling frequencies, which otherwise would degrade the synchronization and localization performance severely.