Distributed collaborative target tracking of UAV formation considering passive detection efficiency

To address the problem of instability and inaccuracy when the Unmanned Aerial Vehicles (UAVs) formation equipped with bearing-only sensor network tracks a maneuvering target, this paper proposes a distributed cooperative tracking control method considering the effectiveness of passive detection. First, the system model of passive detection in UAV formation is constructed. Then, the Geometric Dilution of Precision (GDOP) of bearing-only sensor nodes pair on the observation plane is analyzed. Building on this foundation, the pairwise form is expanded to obtain the optimal geometric configuration for the entire network. Subsequently, the Distributed Cubature Information Filtering (DCIF) is integrated with the weighted average consensus protocol to design the distributed cooperative observer suitable for the system model, enabling state estimation of the target. Finally, within the distributed architecture, the Nonlinear Model Predictive Controller (NMPC) is designed. This controller autonomously assembles the UAV formation during the assembly phase and forms an optimal detection array. The UAV formation then tracks the target using the virtual geometric center based on the established rigid geometric configuration. The simulation experiments validate that the proposed model and method can enhance the passive detection effectiveness of the UAV formation, thereby achieving stable and efficient distributed cooperative tracking for the maneuvering target.

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Publication Details

Journal
Chinese Journal of Aeronautics
Published
2025-03-28
DOI
https://doi.org/10.1016/j.cja.2025.103513
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Distributed collaborative target tracking of UAV formation considering passive detection efficiency

Wenxing Fu, Ruiyun Hong, Zhan Chen, W. Ye et al.
Chinese Journal of Aeronautics
Distributed Control Multi-Agent Systems
article

Distributed collaborative target tracking of UAV formation considering passive detection efficiency

Wenxing Fu, Ruiyun Hong, Zhan Chen, W. Ye, Ruitao Zhang
article en

Abstract

To address the problem of instability and inaccuracy when the Unmanned Aerial Vehicles (UAVs) formation equipped with bearing-only sensor network tracks a maneuvering target, this paper proposes a distributed cooperative tracking control method considering the effectiveness of passive detection. First, the system model of passive detection in UAV formation is constructed. Then, the Geometric Dilution of Precision (GDOP) of bearing-only sensor nodes pair on the observation plane is analyzed. Building on this foundation, the pairwise form is expanded to obtain the optimal geometric configuration for the entire network. Subsequently, the Distributed Cubature Information Filtering (DCIF) is integrated with the weighted average consensus protocol to design the distributed cooperative observer suitable for the system model, enabling state estimation of the target. Finally, within the distributed architecture, the Nonlinear Model Predictive Controller (NMPC) is designed. This controller autonomously assembles the UAV formation during the assembly phase and forms an optimal detection array. The UAV formation then tracks the target using the virtual geometric center based on the established rigid geometric configuration. The simulation experiments validate that the proposed model and method can enhance the passive detection effectiveness of the UAV formation, thereby achieving stable and efficient distributed cooperative tracking for the maneuvering target.

Chinese Journal of AeronauticsVol. 38(7)
Northwestern Polytechnical University (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 95%
Distributed Control Multi-Agent Systems
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Distributed collaborative target tracking of UAV formation considering passive detection efficiency — Wenxing Fu, Ruiyun Hong, et al. · Chinese Journal of Aeronautics (2025) | TGRS Research Map | TGRS