检索结果-内蒙古大学图书馆

第41届中国控制会议

作者： Qi Zhang Jing Ma School of Mathematics Science Heilongjiang University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,the distributed fusion filtering problem for stochastic uncertain systems with packet-dropping compensation and time-correlated noises is *** time-correlated process and measurement noises are described by the first-order Gaussian-Markov *** uncertainties of model parameters are described by correlated white multiplicative *** the sensor measurement signal is lost over network transmission,its one-step prediction is used for *** on the local filters proposed in the recent literature,the filtering error cross-covariance matrices between any two local filters are ***,a distributed fusion filter weighted by matrices is presented based on the distributed weighted fusion algorithm in the linear minimum variance(LMV) *** simulation results verify the effectiveness of the proposed algorithm.

关键词： Time-correlated noise Packet dropout compensator Cross-covariance matrix distributed fusion filter

来源：评论

学校读者我要写书评

暂无评论

distributed fusion filter for Nonlinear Multi-Sensor Systems With Correlated Noises

引用

IEEE ACCESS 2020年 8卷 39548-39560页

作者： Hao, Gang Sun, Shuli Heilongjiang Univ Sch Elect Engn Harbin 150080 Peoples R China Key Lab Informat Fus Estimat & Detect Harbin 150080 Heilongjiang Peoples R China

This paper is concerned with distributed fusion (DF) estimation problem for nonlinear multi-sensor systems with correlated noises. Based on a recursive linear minimum variance estimation (RLMVE) framework, a novel filter is developed. It is proved that the RLMVE-based filter and the existing de-correlated filter have the functional equivalence. Then, for multi-sensor cases, cross-covariance matrices between any two local filters are derived. Based on the RLMVE-based filter and cross-covariance matrices, a DF filter weighted by matrices is proposed in the sense of linear minimum variance. Finally, based on the existing de-correlated filter, the algorithm of cross-covariance for de-correlated systems and the DF algorithm weighted by matrices, a de-correlated DF filtering algorithm is proposed. An example verifies the effectiveness of the proposed RLMVE-based DF filter.

关键词： Estimation Nonlinear systems Noise measurement Mathematical model Kalman filters Covariance matrices Gaussian noise Multi-sensor nonlinear system distributed fusion filter cross-covariance matrix linear minimum variance estimation

来源：评论

学校读者我要写书评

暂无评论

Identification and distributed fusion filter for multi-sensor networked systems with stochastic deception attacks

引用

DIGITAL SIGNAL PROCESSING 2024年 151卷

作者： He, Guangyao Sun, Shuli Heilongjiang Univ Sch Elect Engn Harbin 150080 Peoples R China

In the multi-sensor networked systems, each sensor produces its local state estimate based on its own observations, and then sends it to a fusion center (FC) for fusion estimation. During transmitting local state estimates to the fusion center, the data may suffer from stochastic deception attacks from malicious attackers, where the probabilities of attacks and the variances of attack noises are unknown. Using a correlation function method (CFM), the probabilities of attacks and the variances of attack noises in individual channels are identified in parallel. The possibly attacked local state estimate is filtered to reproduce local state estimate in the FC. Using the matrix-weighted fusion algorithm in the linear unbiased minimum variance (LUMV) criterion, a distributed fusion filter is performed based on the reproduced local state estimates. A simulation example illustrates the validity of the algorithms.

关键词： distributed fusion filter Identification Deception attack Correlation function Multi-sensor system

来源：评论

学校读者我要写书评

暂无评论

distributed fusion filter for multi-sensor systems with finite-step correlated noises

引用

INFORMATION fusion 2019年 46卷 128-140页

作者： Tian Tian Sun Shuli Lin Honglei Heilongjiang Univ Dept Automat Harbin 150080 Heilongjiang Peoples R China

This paper addresses the distributed fusion filtering problem for multi-sensor systems with finite-step correlated noises. The process noise and observation noises of different sensors are finite-step auto- and cross-correlated, respectively. Based on the optimal local filtering algorithms that we presented before, the filtering error cross covariance matrices between any two local filters are derived based on an innovation analysis approach. A distributed fusion filter is put forward by using matrix-weighted fusion estimation algorithm in the linear unbiased minimum variance sense. Finally, the proposed algorithms are extended to systems with random parameter matrices. Two simulation examples are given to show the effectiveness of the proposed algorithms.

关键词： distributed fusion filter Finite-step correlated noises Cross-covariance matrix Multi-sensor system Random parameter matrix Innovation analysis approach

来源：评论

学校读者我要写书评

暂无评论

distributed fusion filter for Multi-sensor Descriptor Systems with Multiple Packet Dropouts Based on Prediction Compensation 37

Distributed Fusion Filter for Multi-sensor Descriptor System...

引用

37th Chinese Control Conference (CCC)

作者： Ma, Jing Sun, Shuli Heilongjiang Univ Sch Math Sci Harbin 150080 Heilongjiang Peoples R China Heilongjiang Univ Dept Automat Harbin 150080 Heilongjiang Peoples R China

ISBN: (纸本)9789881563958

This paper is concerned with the distributed fusion filtering problem for descriptor systems with multiple sensors and multiple packet dropouts. When a packet is lost from a sensor to a local processor over an unreliable network, the predictor of the lost packet is used as a compensator. The original high-order descriptor system is transformed into two reduced-order subsystems (ROSs) by a non-singular linear transformation. By using projection theory, local filters (LFs) are presented for two ROSs in the linear unbiased minimum variance (LUMV) sense. The cross-covariance matrices between any two sensor subsystems and between two ROSs are derived to compute fusion weights, respectively. The distributed fusion filters (DFFs) weighted by matrices are presented for two ROSs in the LUMV sense. Then, DFF for the original descriptor system is obtained. A numerical example is used to show the effectiveness of the presented algorithm.

关键词： distributed fusion filter multi-sensor descriptor system packet dropout compensator cross-covariance

来源：评论

学校读者我要写书评

暂无评论

distributed fusion filter for networked stochastic uncertain systems with transmission delays and packet dropouts

引用

SIGNAL PROCESSING 2017年第0期130卷 268-278页

作者： Ma, Jing Sun, Shuli Heilongjiang Univ Sch Math Sci Harbin 150080 Peoples R China Heilongjiang Univ Dept Automat Harbin 150080 Peoples R China

This paper is concerned with the distributed fusion filtering problem for networked stochastic uncertain systems with white multiplicative noises. The measured data of each sensor are transmitted to the local processor over different communication channels with different one-step delay and packet dropout rates. At each moment, the local processor may receive one or two data packets or nothing. Local filters at individual local processors are transmitted to the fusion center to produce a fusion filter. First, a new augmented model with a lower-dimension state vector is developed. Based on the new augmented model, the local optimal linear filter is designed in the linear minimum variance sense. Then, the cross-covariance matrices between any two local filtering errors are derived to compute the fusion weights. At last, the distributed fusion filter is obtained based on the well-known fusion algorithm weighted by matrices in the linear minimum variance sense. Moreover, the steady-state behavior of the proposed distributed fusion filter is analyzed. (C) 2016 Elsevier B.V. All rights reserved.

关键词： distributed fusion filter Random delay Packet dropout Multiplicative noise Steady state

来源：评论

学校读者我要写书评

暂无评论

distributed fusion filter for Multi-sensor Descriptor Systems with Multiple Packet Dropouts Based on Prediction Compensation

Distributed Fusion Filter for Multi-sensor Descriptor System...

引用

第37届中国控制会议

作者： Jing Ma Shuli Sun School of Mathematics Science Heilongjiang University Department of Automation Heilongjiang University

This paper is concerned with the distributed fusion filtering problem for descriptor systems with multiple sensors and multiple packet dropouts. When a packet is lost from a sensor to a local processor over an unreliable network, the predictor of the lost packet is used as a compensator. The original high-order descriptor system is transformed into two reduced-order subsystems（ROSs） by a non-singular linear transformation. By using projection theory, local filters（LFs） are presented for two ROSs in the linear unbiased minimum variance（LUMV） sense. The cross-covariance matrices between any two sensor subsystems and between two ROSs are derived to compute fusion weights, respectively. The distributed fusion filters（DFFs） weighted by matrices are presented for two ROSs in the LUMV sense. Then, DFF for the original descriptor system is obtained. A numerical example is used to show the effectiveness of the presented algorithm.

关键词： distributed fusion filter multi-sensor descriptor system packet dropout compensator cross-covariance

来源：评论

学校读者我要写书评

暂无评论

distributed fusion filter for Networked Multi-sensor Systems with Multiple Random Transmission Delays and Packet Dropouts 36

Distributed Fusion Filter for Networked Multi-sensor Systems...

引用

第36届中国控制会议

作者： Jing Ma Hao Jin School of Mathematics Science Heilongjiang University School of Computer and Information Engineering Harbin University of Commerce

ISBN: (纸本)9781538629185

This paper is concerned with the distributed fusion filtering problem for networked multi-sensor systems with multiple random transmission delays(RTDs) and packet dropouts(PDs).Based on the new model and local filters(LFs)proposed in a recent literature,the distributed fusion filter weighted by scalars(DFFWS) is given in the linear minimum variance(LMV) *** cross-covariance matrices(CCMs) between any two local filtering errors are derived to compute the fusion weights(FWs).The measured data of each sensor are transmitted to the local processor(LP) over different communication channels with different RTD and PD *** each moment,the LP may receive one or multiple data packets or *** at individual LPs are transmitted to the fusion center to obtain a fusion filter.A simulation example shows the effectiveness.

关键词： distributed fusion filter multi-sensor cross-covariance random delay packet dropout

来源：评论

学校读者我要写书评

暂无评论

distributed fusion filter for multi-sensor systems with multiple random measurement delays and packet dropouts 11

Distributed fusion filter for multi-sensor systems with mult...

引用

11th World Congress on Intelligent Control and Automation

作者： Yu Luyang Ma Jing Sun Shuli Heilongjiang Univ Sch Math Sci Harbin Heilongjiang Pr Peoples R China Heilongjiang Univ Sch Elect Engn Harbin Heilongjiang Pr Peoples R China

ISBN: (纸本)9781479958252

This paper studies the distributed optimal fusion estimation problem for multi-sensors systems with multiple measurement delays and packet dropouts. Firstly, we define a new augmented state vector with a lower dimension. Based on the defined state, the local filter (LF) is given. Then, by applying the weighted fusion algorithms in the linear minimum variance sense, three distributed fusion filters weighted by matrix (FFWM), by diagonal matrix (FFWDM) and by scalars (FFWS) are obtained, respectively. The cross-covariance matrices between any two local filtering errors are derived to compute the fusion weights. Finally, simulation research verifies the effectiveness of the proposed distributed fusion filters.

关键词： Measurement delay Packet dropout distributed fusion filter Multi-sensor Networked system

来源：评论

学校读者我要写书评

暂无评论

distributed fusion filtering for multi-sensor systems with correlated random transition and measurement matrices

引用

INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS 2020年第1-2期97卷 263-274页

作者： Caballero-Aguila, Raquel Garcia-Garrido, Irene Linares-Perez, Josefa Univ Jaen Dept Estadist & IO Paraje Las Lagunillas S-N Jaen 23071 Spain Univ Granada Dept Estadist & IO Granada Spain

This paper is concerned with the distributed fusion estimation problem for discrete-time linear stochastic systems with measurements coming from different sensors and correlated random parameter matrices in both the state and measurement equations. At each sampling time, the random state transition parameter matrices are assumed to be correlated at the same sampling time with the measurement random parameter matrices of each sensor. Moreover, the random parameter matrices in the observation equations are one-step auto-correlated and cross-correlated between the different sensors. The additive noises are also assumed to be correlated. Under these assumptions, the distributed fusion filter is designed as the matrix-weighted linear combination of the local least-squares linear filters obtained at every single sensor, using the linear minimum variance optimality criterion. A numerical simulation example considering a two-sensor system with randomly delayed measurements is used to illustrate the applicability of multi-sensor systems with correlated random parameter matrices and analyse the performance of the proposed filtering estimators.

关键词： distributed fusion filter multi-sensor systems random parameter matrices correlated noises random delays

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：