检索结果-内蒙古大学图书馆

Watermarking-Aided dimensionality reduction encryption for distributed fusion estimation against eavesdropping

JOURNAL OF THE FRANKLIN INSTITUTE 2025年第5期362卷

作者： Yang, Yuhang Song, Shenmin Harbin Inst Technol Ctr Control Theory & Guidance Technol Harbin 150001 Peoples R China

The existing defense strategies offer robust protection against eavesdropping attacks. However, in practical engineering scenarios, the system must navigate numerous challenges, particularly when communication resources are limited. Under such constraints, the estimator performance can suffer significantly, especially when faced with both eavesdropping attacks and resource limitations. This decline is due to the lack of effective adaptation mechanisms. To remedy this issue, we propose an encryption method that incorporates watermarking signals and dimensionality reduction techniques. The core principle of this method aims to find a balanced compromise between the performance demands and the resource constraints. Specifically, dimensionality reduction strategy is applied to reduce the information density of the transmitted signal, which alleviates the burden on network bandwidth. Additionally, the incorporation of the watermarking signal not only enhances the complexity of the signal but also maximizes the estimation error for potential eavesdroppers, which ensures the secure transmission of information. A compensation mechanism, which incorporates techniques for watermarking removal and prediction, has been specifically developed for users at the fusion center. This mechanism undergoes rigorous feasibility and boundedness analyses to ensure the robustness of the encryption strategy and estimator. Extensive simulation experiments conduct to validate the effectiveness and superiority of the developed algorithm.

关键词： Eavesdropping attack Encryption Cyber-physical system distributed fusion estimation

来源：评论

学校读者我要写书评

暂无评论

distributed fusion estimation with square-root array implementation for Markovian jump linear systems with random parameter matrices and cross-correlated noises

引用

INFORMATION SCIENCES 2016年第0期370卷 446-462页

作者： Yang, Yanbo Liang, Yan Pan, Quan Qin, Yuemei Yang, Feng Northwestern Polytech Univ Sch Automat Xian 710072 Peoples R China Minist Educ Key Lab Informat Fus Technol Xian 710072 Peoples R China

This study presents the distributed fusion estimation of discrete-time Markovian jump linear systems with random parameter matrices and cross-correlated noises in sensor networks. The recursive linear minimum mean square error estimator is proposed based on the Gram-Schmidt orthogonalization procedure under a centralized framework. In order to avoid the loss of positive semidefiniteness and reduce dynamical range, its square-root array implementation is presented by recursively triangularizing the square roots of relevant positive semidefinite matrices. Furthermore, via the information filter form, the distributed fusion estimation with square-root array implementation is derived from the centralized fusion structure, incorporated with consensus strategy. A maneuvering target tracking simulation in a sensor network validates the proposed method. (C) 2016 Elsevier Inc. All rights reserved.

关键词： Markovian jump systems distributed fusion estimation Linear minimum mean square errorestimator Square-root array implementation Random parameter matrices Cross-correlated noises

来源：评论

学校读者我要写书评

暂无评论

distributed fusion estimation for Stochastic Uncertain Systems With Network-Induced Complexity and Multiple Noise

引用

IEEE TRANSACTIONS ON CYBERNETICS 2022年第9期52卷 8753-8765页

作者： Liu, Li Zhou, Wenju Fei, Minrui Yang, Zhile Yang, Hongyong Zhou, Huiyu Ludong Univ Sch Informat Sci & Elect Engn Yantai 264025 Peoples R China Southwest Jiaotong Univ Yantai Res Inst New Generat Informat Technol Yantai 264025 Peoples R China Shanghai Univ Sch Mechatron Engn & Automat Shanghai Key Lab Power Stn Automat Technol Shanghai 200072 Peoples R China Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen 518055 Peoples R China Univ Leicester Sch Informat Leicester LE1 7RH Leics England

This article investigates an issue of distributed fusion estimation under network-induced complexity and stochastic parameter uncertainties. First, a novel signal selection method based on event trigger is developed to handle network-induced packet dropouts, as well as packet disorders resulting from random transmission delays, where the H-2/H-infinity performance of the system is analyzed in different noise environments. In addition, a linear delay compensation strategy is further employed for solving the complex network-induced problem, which may deteriorate system performance. Moreover, a weighted fusion scheme is used to integrate multiple resources through an error cross-covariance matrix. Several case studies validate the proposed algorithm and demonstrate satisfactory system performance in target tracking.

关键词： distributed fusion estimation network-induced complexity stochastic and deterministic uncertainty transmission delays

来源：评论

学校读者我要写书评

暂无评论

distributed fusion estimation for Linear Time-varying Systems under DoS Attacks and Bounded Noises 38

Distributed Fusion Estimation for Linear Time-varying System...

引用

38th Chinese Control Conference (CCC)

作者： Zhu, Daoping Chen, Bo Yu, Li Zhejiang Univ Technol Dept Automat Hangzhou 310023 Peoples R China Zhejiang Univ Technol Inst Cyberspace Secur Hangzhou 310023 Peoples R China

ISBN: (纸本)9789881563972

This paper is concerned with the distributed fusion estimation problem for linear time-varying systems under denial of service (DoS) attacks and bounded noises, where the distributions of DoS attacks are not required to be known in advance and the bounds of noises also do not need to be known. A successive compensation model is proposed to reduce the performance loss caused by DoS attacks. Then, by searching the minimum upper bound of fusion estimation error at each time, two convex optimization problems are constructed to design the local gains and optimal weighting matrices. Notice that the established convex optimization problems can be easily solved by using the standard software packages. Finally, an illustrative example is employed to show the effectiveness of the proposed methods.

关键词： distributed fusion estimation DoS Attacks Bounded Noises Convex Optimization Time-Varying Systems

来源：评论

学校读者我要写书评

暂无评论

distributed fusion estimation for Multi-rate Multi-sensor Time-delayed Systems with Fading Measurements 38

Distributed Fusion Estimation for Multi-rate Multi-sensor Ti...

引用

38th Chinese Control Conference (CCC)

作者： Lin, Honglei Sun, Shuli Heilongjiang Univ Dept Automat Harbin 150080 Peoples R China Key Lab Informat Fus Estimat & Detect Heilongjian Harbin 150080 Peoples R China

ISBN: (纸本)9789881563972

This paper proposes a distributed fusion estimator for asynchronous multi-rate multi-sensor systems with time delays and fading measurements. The state is updated uniformly and different sensors uniformly sample measurements with different sampling rates, time delays and fading measurement rates. The independent random variables obeying certain probability distributions over different known intervals are employed to describe the fading measurement phenomena. First, a new state space model at measurement sampling points is constructed where the time-delayed system is transformed to a delay-free one with correlated noises in limited time intervals. Then, the real-time optimal local filters at measurement sampling points and at state update points are derived based on the new state space model. Further, estimation error cross-covariance matrices between any two local estimators are derived. Finally, a real-time distributed fusion estimator at state update points is obtained based on the optimal fusion criterion weighed by matrices in the linear unbiased minimum variance sense. A numerical example is given to illustrate the effectiveness of the proposed algorithms.

关键词： distributed fusion estimation multi-rate sampling time delay fading measurement cross-covariance matrix

来源：评论

学校读者我要写书评

暂无评论

distributed fusion estimation Based on Pseudo-measurement for Multi-sensor System

Distributed Fusion Estimation Based on Pseudo-measurement fo...

引用

International Conference on Computational Intelligence and Natural Computing

作者： Jin Xue-bo Du Jing-jing Wang Lei-lei Zhejiang Sci Tech Univ Coll Informat & Elect Hangzhou 310018 Peoples R China

ISBN: (纸本)9780769536453

By considering the relation between local fusion estimation and fusion center, in this paper the estimation from local fusion nodes is regarded as a pseudo-measurement. Then the distributed estimation algorithm is turned to be two-level centralized fusion estimation and the new optimal distributed fusion estimation algorithm is obtained with Kalman filtering form, which in general only centralized estimation method has. Simulations show the developed algorithm has the excellent estimation performance. By the developed algorithm, the distributed multisensor system can be unified with centralized system and make it possible that applying the abundant research result of centralized system to distributed multisensor system.

关键词： local fusion estimation fusion center centralized fusion estimation distributed fusion estimation

来源：评论

学校读者我要写书评

暂无评论

distributed fusion estimation for Uncertain Systems with Cross-correlated Noises and Transmission Delays 11

Distributed Fusion Estimation for Uncertain Systems with Cro...

引用

11th UKACC International Conference on Control (UKACC Control)

作者： Liu, Li Yang, Aolei Fei, Minrui Tu, Xiaowei Naeem, Wasif Shanghai Univ Sch Mechatron Engn & Automat Shanghai Key Lab Power Stn Automat Technol Shanghai 200072 Peoples R China Queens Univ Belfast Elect Engn & Comp Sci Twentieth Century Fox Belfast BT9 5AH Antrim North Ireland

ISBN: (纸本)9781467398916

The information fusion estimation problems are investigated for uncertain systems with cross-correlated noises and data transmission delays. Based on Kalman filtering theory, a distributed fusion estimation scheme is proposed by distributed information perception and centralized fusion. To alleviate the communication burden and computational cost with network-induced transmission delays, the measurement transformation approach with re-organized innovation sequence is proposed. Depending on the fusion criterion, the optimal weighted fusion estimators are designed via minimizing error cross-covariance theory to reduce information redundancy and maintain the higher measurement accuracy. An illustrative example is given to validate the effectiveness of the proposed method.

关键词： distributed fusion estimation robust Kalman filtering cross-correlated noises transmission delays

来源：评论

学校读者我要写书评

暂无评论

distributed fusion estimation for Multi-sensor Non-uniform Sampling Systems with Correlated Noises and Fading Measurements 36

Distributed Fusion Estimation for Multi-sensor Non-uniform S...

引用

20th International Conference on Information fusion (fusion)

作者： Lin, Honglei Sun, Shuli Heilongjiang Univ Dept Automat Harbin Heilongjiang Peoples R China

ISBN: (数字)9789881563934

ISBN: (纸本)9780996452700

This paper is concerned with the distributed fusion estimation problem for a class of multi-sensor non-uniform sampling systems with correlated noises and fading measurements. The state is updated uniformly and the sensors sample measurement data randomly. The process noise and different measurement noises are correlated at the same instant. Moreover, the fading measurement phenomena may occur in different sensor channels. The independent random variables obeying different certain probability distributions over different known intervals are employed to describe the phenomena. Based on the measurement augmentation method, the state space model is reconstructed in which the asynchronous sampling estimation problem is transformed to the synchronous one. Afterwards, local optimal filters are designed by using an innovation analysis approach. Then, the filtering error cross-covariance matrices between any two local filters are derived. At last, the optimal matrix-weighted distributed fusion filter is given in the linear unbiased minimum variance sense. Simulation results show the effectiveness of the proposed algorithms.

关键词： distributed fusion estimation multi-sensor non-uniform sampling system correlated noise fading measurement cross-covariance matrix

来源：评论

学校读者我要写书评

暂无评论

Networked distributed fusion estimation under uncertain outputs with random transmission delays, packet losses and multi-packet processing

引用

SIGNAL PROCESSING 2019年 156卷 71-83页

作者： Caballero-Aguila, R. Hermoso-Carazo, A. Linares-Perez, J. Univ Jaen Dept Estadist & IO Paraje Las Lagunillas S-N Jaen 23071 Spain Univ Granada Dept Estadist & IO Campus Fuentenueva S-N E-18071 Granada Spain

This paper investigates the distributed fusion estimation problem for networked systems whose multisensor measured outputs involve uncertainties modelled by random parameter matrices. Each sensor transmits its measured outputs to a local processor over different communication channels and random failures -one-step delays and packet dropouts- are assumed to occur during the transmission. White sequences of Bernoulli random variables with different probabilities are introduced to describe the observations that are used to update the estimators at each sampling time. Due to the transmission failures, each local processor may receive either one or two data packets, or even nothing and, when the current measurement does not arrive on time, its predictor is used in the design of the estimators to compensate the lack of updated information. By using an innovation approach, local least-squares linear estimators (filter and fixed-point smoother) are obtained at the individual local processors, without requiring the signal evolution model. From these local estimators, distributed fusion filtering and smoothing estimators weighted by matrices are obtained in a unified way, by applying the least-squares criterion. A simulation study is presented to examine the performance of the estimators and the influence that both sensor uncertainties and transmission failures have on the estimation accuracy. (C) 2018 Elsevier B.V. All rights reserved.

关键词： distributed fusion estimation Covariance information Random measurement matrices Random delays Packet dropouts

来源：评论

学校读者我要写书评

暂无评论

Stochastic Event-Triggered distributed fusion estimation Under Jamming Attacks

引用

IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS 2021年 7卷 309-321页

作者： Li, Li Niu, Mengfei Xia, Yuanqing Yang, Hongjiu Yanshan Univ Sch Elect Engn Qinhuangdao 066004 Hebei Peoples R China Southeast Univ Sch Cyber Sci & Engn Nanjing 210096 Peoples R China Yanshan Univ Sch Elect Engn Qinhuangdao 066004 Hebei Peoples R China Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China Tianjin Univ Sch Elect & Informat Engn Tianjin Key Lab Proc Measurement & Control Tianjin 300072 Peoples R China

The paper concentrates on the distributed fusion estimation issue of a bandwidth-constrained multi-sensor nonlinear networked system suffering from jamming attacks. For each communication channel, a stochastic event-triggered transmission scheme is developed to reduce excessive communication between smart sensors and local estimators, and a Stackelberg game framework is established to analyze interactions between the smart jammer and smart sensors. Utilizing a sequential fast covariance intersection fusion rule, a distributed fusion estimation algorithm is designed by fusing local estimations from event-triggered unscented Kalman filter-based local estimators. Then convergence conditions are derived by analyzing behaviors of the fusion estimation error covariance, and the boundedness of communication rate for each communication channel is further discussed. Finally, a comparative simulation is given to testify the validity of the proposed fusion technique.

关键词： distributed fusion estimation stochastic event-triggered transmission scheme jamming attacks unscented Kalman filter

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：