High-precision Time Synchronization Algorithm for Unmanned Aerial Vehicle Ad Hoc Networks based on Bidirectional Pseudo-range Measurements

Bai, Kaiyuan; Wu, Jianfeng; Wu, Huabing

doi:10.1016/j.adhoc.2023.103326

Cited by 3 publications

(2 citation statements)

References 28 publications

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“…From the perspective of graph theory, the investigation into time synchronization within UANETs inherently revolves around the consensus problem [16]. Furthermore, insights from research conducted in domains such as sensor network time synchronization, the collaborative control of multi-agent systems, and UAV swarm flight can provide valuable guidance and references for addressing the consensus problem [17][18][19][20][21][22].…”

Section: Related Workmentioning

confidence: 99%

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Advancing Convergence Speed of Distributed Consensus Time Synchronization Algorithms in Unmanned Aerial Vehicle Ad Hoc Networks

Wu,

Bai,

2024

Drones

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Time synchronization is a critical prerequisite for unmanned aerial vehicle ad hoc networks (UANETs) to facilitate navigation and positioning, formation control, and data fusion. However, given the dynamic changes in UANETs, improving the convergence speeds of distributed consensus time synchronization algorithms with only local information poses a major challenge. To address this challenge, this study first establishes a convex model on the basis of graph theory and relevant theories of random matrices to approximate the original problem. Subsequently, three acceleration schemes for consensus algorithms are derived by minimizing the Frobenius norm of the iteration matrix. Additionally, this study provides a new upper bound for constant communication weights and discusses the limitations of existing metrics used to measure the convergence speeds of consensus algorithms. Finally, the proposed schemes are compared with existing ones through simulation. Our results indicate that the three proposed schemes can achieve faster convergence while maintaining high-precision synchronization in scenarios with static or known topological structures of networks. In scenarios where the topological structure of a UANET is time-varying and unknown, the scheme proposed in this paper achieves the fastest convergence speed.

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Section: Related Workmentioning

confidence: 99%

“…Table 9 lists the main simulation settings, with further detailed simulation settings being consistent with our previous work, as shown in [16].…”

Section: Local Information Acceleration Scheme Comparisonmentioning

confidence: 99%

Advancing Convergence Speed of Distributed Consensus Time Synchronization Algorithms in Unmanned Aerial Vehicle Ad Hoc Networks

Wu,

Bai,

2024

Drones

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A collaborative navigation algorithm for UAV Ad Hoc network based on improved sequence quadratic programming and unscented Kalman filtering in GNSS denied area

Tang,

Yang,

Wang

et al. 2025

Measurement

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Provisioning High-Precision Clock Synchronization Between UAVs for Low Latency Networks

Shim,

Joo,

Kim

et al. 2024

IEEE Access

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High-precision Time Synchronization Algorithm for Unmanned Aerial Vehicle Ad Hoc Networks based on Bidirectional Pseudo-range Measurements

Cited by 3 publications

References 28 publications

Advancing Convergence Speed of Distributed Consensus Time Synchronization Algorithms in Unmanned Aerial Vehicle Ad Hoc Networks

Advancing Convergence Speed of Distributed Consensus Time Synchronization Algorithms in Unmanned Aerial Vehicle Ad Hoc Networks

A collaborative navigation algorithm for UAV Ad Hoc network based on improved sequence quadratic programming and unscented Kalman filtering in GNSS denied area

Provisioning High-Precision Clock Synchronization Between UAVs for Low Latency Networks

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