Privacy-preserving push-sum distributed cubature information filter for nonlinear target tracking with switching directed topologies

Zha, Jirong; Han, Liang; Dong, Xiwang; Ren, Zhang

doi:10.1016/j.isatra.2022.10.027

Cited by 8 publications

(4 citation statements)

References 34 publications

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“…At the beginning of CIF, the next state is predicted based on the motion model. The prediction process involves the transformation of Cubature Points (CPs) and the calculation of weights [ 19 ]. When new measurement data are available, CIF calculates the value of CPs on the observation function, as well as the information covariance matrix between the estimated state and the measurement.…”

Section: The Proposed Algorithmsmentioning

confidence: 99%

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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: The Proposed Algorithmsmentioning

confidence: 99%

“…Since then, CIF has gained significant traction in addressing estimation challenges posed by nonlinear systems [ 17 ]. On this basis, with the development of sensor network technology and information fusion technology, centralized CIF (CCIF) [ 18 ] and distributed CIF (DCIF) [ 19 ] algorithms have been further studied.…”

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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“…As a crucial part of collaborative target tracking, the way of data fusion significantly affects the estimation performance [24]. Compared with centralized solutions, distributed state estimation (DSE) [25], [26] based on peer-to-peer interaction among sensor nodes has more development potential due to its high scalability, strong robustness, and low resource consumption [7].…”

Section: Data Fusion For Collaborative Filtersmentioning

confidence: 99%

“…4, i.e., V = {ν 1 , ν 2 , ν 3 , ν 4 }. Based on the given communication topologies, the diffusion weight matrix C k is calculated according to (24). Several parameters utilized in the simulation are listed in Table I, where symbol ψ represents (π/180) 2 .…”

Section: B Simulation Settingsmentioning

confidence: 99%

Diffusion-based Filter for Fast and Accurate Collaborative Tracking with Low Data Transmission

Zha,

Zhou,

Liu

et al. 2024

Preprint

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Privacy‐Preserving Coverage Control for Multiagent Systems with Limited Communication Ranges

Wang,

Song,

Liu

2024

Intl J Robust & Nonlinear

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This work investigates the coverage control problem for networked mobile agents on a circle, considering both limited communication ranges and privacy preservation requirements. The objective of the agents is to cooperatively minimize the coverage cost function, which is the longest time required to arrive at any point on the circle from the optimal locations of the agents. A new confidential interaction protocol is proposed to drive the multiagent system to the optimal configuration. Moreover, the process required to implement the confidential interaction protocol is provided to handle the limited communication ranges during coverage tasks. Under the privacy‐preserving coverage control law, it is proved that networked mobile agents with limited communication ranges can be driven to optimal configuration with guaranteed privacy preservation. Finally, a simulation example is provided.

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Privacy-preserving push-sum distributed cubature information filter for nonlinear target tracking with switching directed topologies

Cited by 8 publications

References 34 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

Diffusion-based Filter for Fast and Accurate Collaborative Tracking with Low Data Transmission

Privacy‐Preserving Coverage Control for Multiagent Systems with Limited Communication Ranges

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