Low-Cost Infrastructure-Free 3D Relative Localization with Sub-Meter Accuracy in Near Field

TL;DR

This paper presents a low-cost, infrastructure-free 3D relative localization framework for UxV applications using onboard UWB sensors, achieving sub-meter accuracy through novel algorithms, theoretical analysis, and field testing.

Contribution

It introduces a new 3D localization approach based solely on onboard UWB sensors, including theoretical bounds, algorithms, and a sensor deployment strategy inspired by animal behavior.

Findings

Achieves sub-meter accuracy in 3D localization

Demonstrates effectiveness through simulations and field tests

Provides a cost-effective solution for UxV systems

Abstract

Relative localization in the near-field scenario is critically important for unmanned vehicle (UxV) applications. Although related works addressing 2D relative localization problem have been widely studied for unmanned ground vehicles (UGVs), the problem in 3D scenarios for unmanned aerial vehicles (UAVs) involves more uncertainties and remains to be investigated. Inspired by the phenomenon that animals can achieve swarm behaviors solely based on individual perception of relative information, this study proposes an infrastructure-free 3D relative localization framework that relies exclusively on onboard ultra-wideband (UWB) sensors. Leveraging 2D relative positioning research, we conducted feasibility analysis, system modeling, simulations, performance evaluation, and field tests using UWB sensors. The key contributions of this work include: derivation of the Cram\'er-Rao lower bound (CRLB) and geometric dilution of precision (GDOP) for near-field scenarios; development of two localization algorithms -- one based on Euclidean distance matrix (EDM) and another employing maximum likelihood estimation (MLE); comprehensive performance comparison and computational complexity analysis against state-of-the-art methods; simulation studies and field experiments; a novel sensor deployment strategy inspired by animal behavior, enabling single-sensor implementation within the proposed framework for UxV applications. The theoretical, simulation, and experimental results demonstrate strong generalizability to other 3D near-field localization tasks, with significant potential for a cost-effective cross-platform UxV collaborative system.