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Zonotopic distributed fusion Over Binary Sensor Networks With Bit Rate Allocation: A CodingDecoding Approach

IEEE TRANSACTIONS ON CYBERNETICS 2024年第11期54卷 6855-6866页

作者： Lan, Lan Wei, Guoliang Ding, Derui Zhang, Jiayi Univ Shanghai Sci & Technol Coll Sci Shanghai 200093 Peoples R China Univ Shanghai Sci & Technol Sch Business Shanghai 200093 Peoples R China Univ Shanghai Sci & Technol Dept Control Sci & Engn Shanghai 200093 Peoples R China

In this article, the zonotopic distributed fusion estimation problem is investigated for a class of general nonlinear systems over binary sensor networks subject to unknown-but-bounded (UBB) noises. The network communication from nodes to the fusion center is confined to the limited bit rate. To alleviate the impact from less measurement information of the binary sensor, a modified innovation is constructed to improve the estimation accuracy. Then, a novel coding-decoding approach is proposed to ensure that the decoder has the ability to decode information from each node. Based on the matrix weighting fusion method, a distributed fusion algorithm is put forward under the zonotopic set-membership filtering framework, and the F-radius of the local zonotopic sets are derived and minimized by selecting the filtering gain parameters. Moreover, the bit rate allocation scheme and the weighting coefficients are determined by resolving two optimization problems. In addition, a sufficient condition is established to guarantee the uniform boundedness of the F-radius of the fused zonopotic. Finally, the ballistic object tracking systems is utilized to illustrate the availability of the presented algorithm.

关键词： estimation Bit rate Resource management Noise Decoding Accuracy Bandwidth Binary sensor bit rate constraints coding-decoding distributed fusion estimation zonotopic

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New distributed fusion filtering algorithm based on covariances over sensor networks with random packet dropouts

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2017年第9期48卷 1805-1817页

作者： Caballero-Aguila, R. Hermoso-Carazo, A. Linares-Perez, J. Univ Jaen Dept Estadist & IO Jaen Spain Univ Granada Dept Estadist & IO Granada Spain

This paper studies the distributed fusion estimation problem from multisensor measured outputs perturbed by correlated noises and uncertainties modelled by random parameter matrices. Each sensor transmits its outputs to a local processor over a packet-erasure channel and, consequently, random losses may occur during transmission. Different white sequences of Bernoulli variables are introduced to model the transmission losses. For the estimation, each lost output is replaced by its estimator based on the information received previously, and only the covariances of the processes involved are used, without requiring the signal evolution model. First, a recursive algorithm for the local least-squares filters is derived by using an innovation approach. Then, the cross-correlation matrices between any two local filters is obtained. Finally, the distributed fusion filter weighted by matrices is obtained from the local filters by applying the least-squares criterion. The performance of the estimators and the influence of both sensor uncertainties and transmission losses on the estimation accuracy are analysed in a numerical example.

关键词： distributed fusion estimation covariance information random parameter matrices correlated noises packet dropouts

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Information fusion algorithms for state estimation in multi-sensor Systems with correlated missing measurements

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APPLIED MATHEMATICS AND COMPUTATION 2014年 226卷 548-563页

作者： Caballero-Aguila, R. Garcia-Garrido, I. Linares-Perez, J. Univ Jaen Dept Estadist & IO Jaen 23071 Spain Univ Granada Dept Estadist & IO E-18071 Granada Spain

In this paper, centralized and distributed fusion estimation problems in linear discrete-time stochastic systems with missing observations coming from multiple sensors are addressed. At each sensor, the Bernoulli random variables describing the phenomenon of missing observations are assumed to be correlated at instants that differ m units of time. By using an innovation approach, recursive linear filtering and fixed-point smoothing algorithms for the centralized fusion problem are derived in the least-squares sense. The distributed fusion estimation problem is addressed based on the distributed fusion criterion weighted by matrices in the linear minimum variance sense. For each sensor subsystem, local least-squares linear filtering and fixed-point smoothing estimators are given and the estimation error cross-covariance matrices between any two sensors are derived to obtain the distributed fusion estimators. The performance of the proposed estimators is illustrated by numerical simulation examples where scalar and two-dimensional signals are estimated from missing observations coming from two sensors, and the estimation accuracy is analyzed for different missing probabilities and different values of m. (C) 2013 Elsevier Inc. All rights reserved.

关键词： Least-squares estimation Centralized fusion estimation distributed fusion estimation Missing observations Multi-sensor systems

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Energy-Constrained Confidentiality fusion estimation Against Eavesdroppers

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2022年第2期69卷 624-628页

作者： Xu, Daxing Yan, Xinhao Chen, Bo Yu, Li Zhejiang Univ Technol Coll Informat Engn Hangzhou 310023 Peoples R China Quzhou Univ Coll Elect & Informat Engn Quzhou 324000 Peoples R China

This brief studies energy-constrained confidentiality fusion estimation problem in presence of eavesdroppers, where all data that is transmitted from sensors to fusion center may be collected by eavesdroppers through wireless channels. To prevent eavesdropping, an injection method based on artificial noise is proposed, but the insertion of noises will consume more sensor energy, which can add the design difficulty under energy constraints. In this case, the stochastic sensor data triggers are adopted to reduce the communication rate between the local sensors and the fusion center. Subsequently, a sufficient condition is derived to guarantee the effective noise insertion strategy under certain triggers. Moreover, by selecting appropriate trigger threshold for each sensor with fixed encryption level, it is derived that how to make the eavesdroppers' local/fusion estimation error covariance unbound while the user's expected error remains the boundedness. Finally, the single generator infinite power system is employed to show the effectiveness of the proposed methods.

关键词： estimation Eavesdropping Signal to noise ratio Data privacy Decoding Circuits and systems Channel estimation Artificial noise eavesdropping energy constraints distributed fusion estimation cyber-physical systems

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Parallel Covariance Intersection fusion Optimal Kalman Filter

Parallel Covariance Intersection Fusion Optimal Kalman Filte...

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2nd International Conference on Sensors, Measurement and Intelligent Materials (ICSMIM 2013)

作者： Zhang, Peng Qi, Wenjuan Deng, Zili Heilongjiang Univ Dept Automat Harbin 150080 Peoples R China

ISBN: (纸本)9783037859711

For multisensor network systems with unknown cross-covariances, a novel multi-level parallel covariance intersection (PCI) fusion Kalman filter is presented in this paper, which is realized by the multi-level parallel two-sensor covariance intersection (CI) fusers, so it only requires to solve the optimization problems of several one-dimensional nonlinear cost functions in parallel with loss computation burden. It can significantly reduce the computation time and increase data processing rate when the number of sensors is very large. It is proved that the PCI fuser is consistent, and its accuracy is higher than that of each local filter and is lower than that of the optimal Kalman fuser weighted by matrices. The geometric interpretation of accuracy relations based on the covariance ellipses is given. A simulation example for tracking systems verifies the accuracy relations.

关键词： Multisensor information fusion parallel processing distributed fusion estimation Kalman filters

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Secure fusion estimation Against Eavesdroppers 37

Secure Fusion Estimation Against Eavesdroppers

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37th Chinese Control Conference (CCC)

作者： Xu, Daxing Chen, Bo Yu, Li Zhejiang Univ Technol Dept Automat Hangzhou 310023 Zhejiang Peoples R China Quzhou Univ Coll Elect & Informat Engn Quzhou 324000 Peoples R China

ISBN: (纸本)9789881563958

This paper studies distributed secure fusion estimation problem in presence of eavesdroppers, where an eavesdropper can collect the messages from sensors to the fusion center through communication networks. To prevent eavesdropping, an insertion method of artificial noises is developed based on the fusion estimation error covariance matrix such that: i) The local/fusion estimation error covariance of the eavesdropper is unbounded;ii) The fusion estimation error covariance of the defender is bounded. Moreover, a sufficient condition is derived to guarantee the effective noise insertion strategy. Simulations are given to show the effectiveness of the proposed methods.

关键词： Artificial noise Eavesdropping Sensor fusion distributed fusion estimation

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An Improved Range Parameterized Square Root Cubature Information Filter Algorithm for Multi-UAV Cooperative Passive Location

An Improved Range Parameterized Square Root Cubature Informa...

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IEEE International Conference on Information and Automation 2015

作者： Zhou, Deyun Zhang, Hao Pan, Qian Zhang, Kun Northwestern Polytech Univ Sch Elect & Informat Xian Shanxi Province Peoples R China

ISBN: (纸本)9781467391047

In order to improve the deficiency of range information unmeasurable in passive location and high computational complexity in distributed fusion estimation, an improved range parameterized square root cubature information filter (RP-SRCIF) algorithm is proposed. The proposed algorithm adopts fully distributed fusion estimation structure, integrates square root cubature Kalman filter (SRCKF) algorithm, range parameterized method and information filter (IF) algorithm. SRCKF can ensure better numerical stability and higher estimation accuracy;the improved range parameterized method can provide good robustness for initial estimation range and better real-time performance than traditional range parameterized method;IF with fully distributed fusion estimation structure makes fusion estimation computation more simple and convenient. Simulation results indicate the RP-SRCIF algorithm is feasible and more effective when compared with other algorithms for multi-UAV cooperative passive location.

关键词： passive location distributed fusion estimation range parameterized square root cubature information filter

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Multi-rate distributed fusion estimate of sensor networks based on descriptor system 27

Multi-rate distributed fusion estimate of sensor networks ba...

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27th Chinese Control and Decision Conference, CCDC 2015

作者： Lei, Zhu Dong-Mei, Zhang College of Science Zhejiang University of Technology Hangzhou China

ISBN: (纸本)9781479970179

This paper presents a distributed estimate and fusion algorithm for the sensor networks whose nodes obey the descriptor system model. Firstly, the singular value decomposition is used to transform the singular system into two equivalent reduced order sub-systems, which yields a set of multi-rate systems by using the multi-rate sampling scheme. The local Kalman estimators and the filtering error covariance matrices are then obtained by means of the re-organized innovation and the orthogonal projection principle. The fusion estimators are further proposed with a fusion rule weighted by matrices. The algorithm presented in this paper is more precise than the local estimator with the signal sensor. Finally, numerical examples are presented to illustrate the feasibility and effectiveness of the proposed algorithm. © 2015 IEEE.

关键词： Descriptor system distributed fusion estimation Multi-rate sampling scheme Orthogonal projection principle

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Multi-rate distributed fusion estimate of sensor networks based on descriptor system

Multi-rate distributed fusion estimate of sensor networks ba...

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27th Chinese Control and Decision Conference (CCDC)

作者： Zhu Lei Zhang Dong-mei Zhejiang Univ Technol Coll Sci Hangzhou 310023 Zhejiang Peoples R China

ISBN: (纸本)9781479970162

关键词： Descriptor system Multi-rate sampling scheme Orthogonal projection principle distributed fusion estimation

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Secure fusion estimation Against Eavesdroppers

Secure Fusion Estimation Against Eavesdroppers

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第37届中国控制会议

作者： Daxing Xu Bo Chen Li Yu Department of Automation Zhejiang University of Technology College of Electrical and Information Engineering Quzhou University

This paper studies distributed secure fusion estimation problem in presence of eavesdroppers, where an eavesdropper can collect the messages from sensors to the fusion center through communication networks. To prevent eavesdropping,an insertion method of artificial noises is developed based on the fusion estimation error covariance matrix such that: i) The local/fusion estimation error covariance of the eavesdropper is unbounded;ii) The fusion estimation error covariance of the defender is bounded. Moreover, a sufficient condition is derived to guarantee the effective noise insertion strategy. Simulations are given to show the effectiveness of the proposed methods.

关键词： Artificial noise Eavesdropping Sensor fusion distributed fusion estimation

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