Distributed Maximum Correntropy Cubature Information Filtering for Tracking Unmanned Aerial Vehicle

Zhou, Yu Hua; Zheng, Zhili; Huang, Jing; Wang, Chengjun; Xu, Guangbo; Xuchen, Youshi; Zha, Bingting

doi:10.1109/jsen.2023.3261180

Cited by 6 publications

(1 citation statement)

References 41 publications

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“…In engineering applications, CIF with better effects is applied to locate targets [ 20 ]. CIF is also widely used in the location of passive sensor networks in the fields of aviation [ 21 ], spaceflight [ 22 ] and navigation [ 23 ].…”

Section: Introductionmentioning

confidence: 99%

Distributed Cubature Information Filtering Method for State Estimation in Bearing-Only Sensor Network

Chen,

Fu,

Zhang

et al. 2024

Entropy

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The problem of state estimation based on bearing-only sensors is increasingly important while existing research on distributed filtering solutions is rather limited. Therefore, this paper proposed the novel distributed cubature information filtering (DCIF) method for addressing the state estimation challenge in bearing-only sensor networks. Firstly, the system model of the bearing-only sensor network was constructed, and the observability of the system was analyzed. The sensor nodes are paired to measure relative angle information. Subsequently, the coordinated consistency theory is employed to achieve a unified state estimation of the maneuvering target. The DCIF method enhances the observability of the system, addressing the issues of large accuracy errors and divergence in traditional nonlinear filtering algorithms. Building upon the theoretical proof of consistency convergence in DCIF, four simulation experiments were conducted for comparison. These experiments validate the effectiveness and superiority of the DCIF method in bearing-only sensor networks.

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Section: Introductionmentioning

confidence: 99%

Distributed Cubature Information Filtering Method for State Estimation in Bearing-Only Sensor Network

Chen,

Fu,

Zhang

et al. 2024

Entropy

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Maximum weighted correntropy filters for nonlinear non‐Gaussian systems

Liu,

Zhang,

Song

2024

Asian Journal of Control

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In this paper, we focus on the filtering issue for nonlinear non‐Gaussian systems. Considering the limitations of the Gaussian function with a single kernel bandwidth, we design a novel extended version called weighted Gaussian function, which consists of a weighting coefficient and two distinct kernel bandwidths. The additional coefficient can directly balance two kernel bandwidths, which improves the flexibility and performance of the correntropy. We develop a cost function utilizing the suggested weighted Gaussian function and statistical linearization method, followed by deriving a maximum weighted correntropy filter based on the maximum correntropy criterion. The proposed algorithm is demonstrated to converge to a Gaussian filter as the kernel bandwidths approach infinity. In addition, we derive the corresponding information filter, which takes the form of information matrix and information vector. It is computationally efficient and easier to generalize to multisensor systems. The performance of the proposed algorithms is compared with other filters based on the third‐order spherical cubature rule and the fixed point iteration technique in a target tracking system. Simulation results confirm the effectiveness of the new approaches.

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Distributed cooperative tracking and cooperative guidance against maneuvering aerial target

Zhang,

Dong,

et al. 2024

Aerospace Science and Technology

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Distributed Maximum Correntropy Cubature Information Filtering for Tracking Unmanned Aerial Vehicle

Cited by 6 publications

References 41 publications

Distributed Cubature Information Filtering Method for State Estimation in Bearing-Only Sensor Network

Distributed Cubature Information Filtering Method for State Estimation in Bearing-Only Sensor Network

Maximum weighted correntropy filters for nonlinear non‐Gaussian systems

Distributed cooperative tracking and cooperative guidance against maneuvering aerial target

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