Data set for UWB Cooperative Navigation and Positioning of UAV Cluster

The cooperative navigation of unmanned aerial vehicle (UAV) cluster has become a popular topic in military and civilian applications. Ultra-wideband (UWB) technology provides a precise and stable practical solution for distance-based cooperative positioning. To develop and evaluate the cooperative navigation system for UAVs, this paper utilizes eight fixed base stations and seven mobile UAVs to collect measurement results under four different flight formations in both indoor and outdoor environments. To eliminate fluctuations in UAV control, predefined flight trajectories were used, and multiple measurements were collected at each trajectory point for technical validation. The resulting data supports the development and validation of distance-based multi-target navigation algorithms, the evaluation of formation maintenance and collision avoidance algorithms for multiple UAVs, and also serves as a source for navigation evaluation and the development of multi-source fusion cluster positioning algorithms.

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Publication Details

Journal
Scientific Data
Published
2025-03-23
DOI
https://doi.org/10.1038/s41597-025-04808-0
Citations
11
Primary Topic
Indoor and Outdoor Localization Technologies
Type
article
Field-Weighted Citation Impact
8.03

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Data set for UWB Cooperative Navigation and Positioning of UAV Cluster

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article

Data set for UWB Cooperative Navigation and Positioning of UAV Cluster

Chengkai Tang, Cunle Zhang, Baowang Lian, Haonan Wang, Lingling Zhang
article en
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Abstract

The cooperative navigation of unmanned aerial vehicle (UAV) cluster has become a popular topic in military and civilian applications. Ultra-wideband (UWB) technology provides a precise and stable practical solution for distance-based cooperative positioning. To develop and evaluate the cooperative navigation system for UAVs, this paper utilizes eight fixed base stations and seven mobile UAVs to collect measurement results under four different flight formations in both indoor and outdoor environments. To eliminate fluctuations in UAV control, predefined flight trajectories were used, and multiple measurements were collected at each trajectory point for technical validation. The resulting data supports the development and validation of distance-based multi-target navigation algorithms, the evaluation of formation maintenance and collision avoidance algorithms for multiple UAVs, and also serves as a source for navigation evaluation and the development of multi-source fusion cluster positioning algorithms.

Scientific DataVol. 12(1)
Northwestern Polytechnical University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 2%
Indoor and Outdoor Localization Technologies
8.03
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