Neighborhood Selection Synchronization Mechanism-Based Moving Source Localization Using UAV Swarm

To obtain the accurate time difference of arrival (TDOA) and frequency difference of arrival (FDOA) for passive localization in an unmanned aerial vehicle (UAV) swarm, UAV swarm network synchronization is necessary. However, most of the traditional distributed time synchronization protocols are base...

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Published inRemote sensing (Basel, Switzerland) Vol. 15; no. 9; p. 2313
Main Authors Zhou, Yongkun, Gao, Wei, Rao, Bin, Ding, Bowen, Wang, Wei
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 27.04.2023
Subjects
Accuracy
Algorithms
Communication
Convergence
Crystal oscillators
Drone aircraft
Energy consumption
Global positioning systems
GPS
Iterative methods
Localization
Localization method
moving source
Neighborhoods
passive localization
Protocol
Radiation
Radiation sources
Remote sensing
Synchronization
Time synchronization
UAV swarm NS-AS synchronization mechanism
Unmanned aerial vehicles
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Summary:To obtain the accurate time difference of arrival (TDOA) and frequency difference of arrival (FDOA) for passive localization in an unmanned aerial vehicle (UAV) swarm, UAV swarm network synchronization is necessary. However, most of the traditional distributed time synchronization protocols are based on iteration, which hinders efficiency improvement. High communication costs and long convergence times are often required in large-scale UAV swarm networks. This paper presents a neighborhood selection-all selection (NS-AS) synchronization mechanism-based moving source localization method for UAV swarms. First, the NS-AS synchronization mechanism is introduced, to model the UAV swarm network synchronization process. Specifically, the UAV neighbors are first grouped by sector, and the most representative neighbors are selected from each sector for the state update calculation. When the UAV swarm network reaches a fully connected state, the synchronization mechanism is switched to select all neighbors, to improve the convergence speed. Then, the TDOA-FDOA joint localization algorithm is employed to locate the moving radiation source. Through simulation, the effectiveness of the proposed method is verified by the system convergence and localization performance under different parameters. Experimental results show that the synchronization mechanism based on NS-AS effectively improves the convergence speed of the system while ensuring the accuracy of moving radiation source localization.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs15092313