# A High-Precision Cooperative Localization Method for UAVs Based on Multi-Condition Constraints

## TL;DR

This paper introduces a new method for improving drone localization accuracy by combining aerial and ground-based systems, reducing vertical errors significantly.

## Contribution

The novel air–ground cooperative system with edge-deployed ground stations reduces vertical localization drift in UAV swarms.

## Key findings

- Pure air-based swarms have Z-axis errors of 3.0–5.0 m due to insufficient vertical baselines.
- Air–ground cooperation reduces Position Dilution of Precision to 0.754, improving vertical accuracy.
- Optimized geometric configurations outperform sensor redundancy in cost–benefit ratio.

## Abstract

What are the main findings?
Pure air-based swarm configurations suffer from significant Z-axis error divergence (3.0–5.0 m) due to insufficient vertical baselines, which cannot be resolved by merely increasing the swarm scale.The proposed air–ground cooperative system with edge-deployed ground stations reduces the Position Dilution of Precision (PDOP) to 0.754, effectively suppressing vertical localization drift.

Pure air-based swarm configurations suffer from significant Z-axis error divergence (3.0–5.0 m) due to insufficient vertical baselines, which cannot be resolved by merely increasing the swarm scale.

The proposed air–ground cooperative system with edge-deployed ground stations reduces the Position Dilution of Precision (PDOP) to 0.754, effectively suppressing vertical localization drift.

What are the implications of the main findings?
Geometric configuration optimization offers a superior cost–benefit ratio compared to sensor redundancy, proving that the “quality of geometry” outweighs the “quantity of nodes”.The established “Stereo Air-Based + Edge Ground-Based” strategy provides a robust engineering paradigm for precise localization in GNSS-denied environments.

Geometric configuration optimization offers a superior cost–benefit ratio compared to sensor redundancy, proving that the “quality of geometry” outweighs the “quantity of nodes”.

The established “Stereo Air-Based + Edge Ground-Based” strategy provides a robust engineering paradigm for precise localization in GNSS-denied environments.

Global Navigation Satellite Systems (GNSSs) often suffer from significant localization errors in signal-denied environments. Furthermore, the accuracy of multi-UAV cooperative localization is highly sensitive to the relative geometric configuration of the swarm. To address these challenges, this paper proposed a novel high-precision and robust cooperative localization method for UAVs. The proposed method comprised two key modules. First, based on the principle of minimizing the Geometric Dilution of Precision, we optimized both the quantity and geometric configuration of the UAV swarm to identify the top three optimal aerial formations. Second, we introduced Ground-Assisted Reference Stations or Unmanned Ground Vehicles to establish an air–ground cooperative localization system. By leveraging Time Difference of Arrival constraints, this system significantly enhanced localization accuracy and robustness. From this analysis, two optimal hybrid configurations were selected. Experimental results showed that while purely air-based geometric optimization enhanced horizontal coverage, it failed to effectively suppress Z-axis errors due to inadequate vertical baselines, with deviations consistently oscillating between 3.0 m and 5.0 m. Conversely, the introduction of edge-deployed ground reference stations reduced the Position Dilution of Precision to a remarkably low level of 0.75, effectively suppressing error divergence. This demonstrated that the proposed air–ground cooperative scheme outperformed traditional pure air-based swarm approaches in localization performance. These findings hold significant theoretical and practical value.