Lightweight Node Selection in Hexagonal Grid Topology for TDoA-Based UAV Localization

TL;DR

This paper proposes a lightweight node selection method using RSSI for TDoA-based UAV localization in urban environments, enhancing accuracy and efficiency by dynamically choosing reference nodes.

Contribution

It introduces a novel, energy-efficient node selection strategy based solely on RSSI measurements for improved UAV localization in hexagonal grid deployments.

Findings

Dynamic node selection improves localization accuracy.

The method reduces resource consumption in UAV localization.

Simulation results validate the effectiveness of the approach.

Abstract

This paper investigates the optimization problem for TDoA-based UAV localization in low-altitude urban environments with hexagonal grid node deployment. We derive a lightweight optimized node selection strategy based on only RSSI measurements, to pre-select optimal nodes, avoiding extensive TDoA measurements in energy-constrained UAV scenarios. Theoretical and simulation results demonstrate that dynamically selecting the number of reference nodes improves localization performance while minimizing resource overhead.