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检索条件"主题词=Weighted Measurement Fusion"

共 11 条记录，以下是1-10 订阅

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Reduced dimension weighted measurement fusion Kalman filtering algorithm

Reduced dimension weighted measurement fusion Kalman filteri...

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2009中国控制与决策会议

作者： Chenjian Ran ~1,ZiLi Deng~2 1.Department of Automation,Heilongjiang University,Harbin 150080 2.Department of Automation,Heilongjiang University,Harbin 150080

＜正＞For the multisensor linear discrete time-invariant systems with correlated measurement noises and with dif ferent measurement matrices,based on the linear unbiased minimum variance criterion,a weighted measurement fusion Kalman filtering algorithm is *** is identical to that obtained by the weighted Least Squares（WLS） method, and is numerically identical to the centralized fusion Kalman filtering algorithm,so that it has the global *** optimal weights are given by the Lagrange multiplier method,but its computation burden is *** order to reduce the computational burden,a reduced dimension weighted measurement fusion Kalman filtering algorithm is derived,which avoids the Lagrange multiplier method,and can significantly reduced the computational *** comparison of computational count between two algorithms is given.A simulation example shows effectiveness and correctness of the proposed algorithm.

关键词： weighted measurement fusion Linear unbiased minimum variance(LUMV) criterion Lagrange multiplier method and Reduced dimension algorithm

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Self-tuning weighted measurement fusion Kalman Filter with Cooperating Identification for Multisensor System with Correlated Noises

Self-tuning Weighted Measurement Fusion Kalman Filter with C...

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2011 Chinese Control and Decision Conference（CCDC）

作者： Hao Gang1,Li Yun2,Sun Lai-jun1 (1.Heilongjiang University,Electronic Engineering Institute,Heilongjiang,Harbin,150080,China 2.Harbin University of Commerce,School of Computer and Information Engineering,Heilongjiang,Harbin,150001,China)

For the multisensor system with correlated noises and unknown noise statistics,the measurement function can be dealt with in a unified way to form a new tracking system by least square *** result of the measurements can make some groups of steady random sequence,and the variances Rii and covariance Rij of these measurements can be yielded by the matrix equations of the correlation function,and then the estimates of Qw T can be *** the self-tuning weighted measurement fusion Kalman filter is obtained.A simulation example for a tracking system with 3 sensors shows its fast convergence and exactness.

关键词： Noise statistics estimation Self-tuning Kalman filter weighted measurement fusion

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Robust weighted measurement fusion Kalman Filter with Uncertain Parameters and Noise Variances

Robust Weighted Measurement Fusion Kalman Filter with Uncert...

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2015年中国智能自动化学术会议

作者： Chunshan Yang Zili Deng Department of Automation Heilongjiang UniversityXue Fu Road 74 Heilongjiang University Electronic and Engineering College 130 Department of Computer Science and Technology ChengDong College of Northeast Agricultural University

For the multisensor time-invariant system with both the uncertainties noise variances and parameters, by introducing a fictitious white noise to compensate the uncertain parameters, based on the minimax robust estimation principle and the Lyapunov equation method, a robust weighted measurement fusion Kalman filter is presented. It is proved that for prescribed upper bound variance of fictitious noise, there exists a sufficiently small robust region of uncertain parameter perturbances, such that its actual filtering error variances are guaranteed to have a conservative upper bound. A simulation example shows how to search the robust region, and shows its good performances.

关键词： Uncertain parameters Uncertain noise variances Fictitious white noise weighted measurement fusion Minimax robust Kalman filter

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Two-Level Robust weighted measurement fusion Kalman Filter over Clustering Sensor Network with Uncertain Noise Variances

Two-Level Robust Weighted Measurement Fusion Kalman Filter o...

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2015年中国智能自动化学术会议

作者： Guihuan Nie Peng Zhang Wenjuan Qi Zili Deng Department of Automation Heilongjiang University

Applying the Lyapunov equation method, this paper presents a robust weighted measurement fusion Kalman filter over clustering sensor network with uncertain noise variances, which can significantly reduce the communicational load and save energy when the number of sensors is very large. Its robust accuracy is equal to that of the global centralized robust Kalman fuser or the two-level centralized Kalman fuser, and is higher than those of each local robust Kalman filter and each local robust weighted measurement Kalman fuser. One simulation example is given to verify its effectiveness and correctness.

关键词： Clustering sensor network weighted measurement fusion Robust Kalman filter Uncertain noise variance Robust accuracy

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Robust weighted measurement fusion Kalman filter for uncertain multi-sensor descriptor system with colored measurement noises

Robust weighted measurement fusion Kalman filter for uncerta...

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第40届中国控制会议

作者： Guili Tao Xuemei Wang Wenqiang Liu Jianfei Zhang Haiying Yu College of Media Engineering Communication University of Zhejiang Zhejiang Gongshang University Heilongjiang University of Science and Technology

For uncertain multi-sensor descriptor stochastic linear system with colored measurement noises,by applying the singular value decomposition,the original system can be transformed into two reduced-order subsystems with correlated noises by means of difference transformation of the measurement *** the problem of weighted measurement fusion Kalman filtering is transformed into prediction problem for *** robust weighted measurement fusion time-varying Kalman predictor is presented for the first *** on the relationship between subsystems and original system,the robust weighted measurement fusion Kalman filter of the original multi-sensor descriptor system is *** effectiveness of the proposed algorithm is verified by a numerical simulation example.

关键词： Multi-sensor descriptor system weighted measurement fusion uncertain noise variances colored noises robust Kalman filter

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Self-tuning weighted measurement fusion Wiener Filter and Its Convergence

Self-tuning Weighted Measurement Fusion Wiener Filter and It...

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2009中国控制与决策会议

作者： Yuan Gao,Weiling Wang,Zili Deng Department of Automation,Heilongjiang University,Harbin 150080,China

For the multisensor system with identical measurement matrix and correlated measurement noises,by correlated method,the online estimators of the noise statistics are *** on modern time series analysis method,a self-tuning weighted measurement fusion Wiener filter is presented,which avoids Lyapunov and Riccati equations,reduces the computational burden and is suitable for real time *** dynamic error system analysis (DESA) method,it is rigorously proved that the proposed self-tuning Wiener filter converges to the optimal Wiener filter in a realization or with probability one,*** has asymptotical global optimality.A simulation example for a target tracking systems with 3 sensors shows its effectiveness.

关键词： weighted measurement fusion Self-tuning Wiener Filter Convergence Dynamic Error System Analysis(DESA) Method Modem Time Series Analysis Method

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Self-tuning measurement fusion White Noise Deconvolution Estimator

Self-tuning Measurement Fusion White Noise Deconvolution Est...

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2009中国控制与决策会议

作者： Xiaojun Sun,Zili Deng Department of Automation,Heilonejiang University,Harbin 150080,China

White noise deconvolution or input white noise estimation has a wide range of applications including oil seismic exploration,communication,signal processing,and state *** the multisensor linear discrete time-invariant stochastic systems with correlated measurement noises and unknown noise statistics,an on-line noise statistics estimator is presented by using the correlation *** on the self-tuning Riccati equation,a self-tuning weighted measurement fusion white noise deconvolution estimator is presented using the Kalman filtering *** is proved that the self-tuning fusion white noise deconovlution estimator converges to the optimal fusion steady-state white noise deconvolution estimator in a realization by the dynamic error system analysis(DESA) method,so that it has the asymptotic global optimality.A simulation example for a tracking system with 3 sensors shows its effectiveness.

关键词： Multisensor Information fusion weighted measurement fusion Self-tuning Fuser White Noise Deconvolution Asymptotic Global Optimality Kalman Filtering Convergence

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Steady-state Optimal measurement fusion White Noise Deconvolution Estimators

Steady-state Optimal Measurement Fusion White Noise Deconvol...

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2009中国控制与决策会议

作者： Xiao-Jun Sun,Zi-Li Deng Department of Automation,Heilongjiang University,Harbin 150080,China

White noise deconvolution or input white noise estimation has a wide range of applications including oil seismic exploration,communication,signal processing,and state *** the multisensor linear discrete time-invariant stochastic systems with correlated measurement noises,a steady-state measurement fusion system is obtained by the weighted least square(WLS) method.A steady-state optimal weighted measurement fusion white noise deconvolution estimator is presented using the Kalman filtering *** a new derivation method,it is rigorously proved that the steady-state white noise deconvolution fuser is numerically identical to the centralized steady-state white noise deconvolution fuser,*** has the asymptotically global *** can reduce the computational burden because of the lower dimension of the measurement vector.A simulation example for the Bernoulli-Gaussian input white noise shows the effectiveness of the proposed results.

关键词： Multisensor Information fusion weighted measurement fusion White Noise Deconvolution Global Optimality Kalman Filtering

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Reduced Dimension measurement fusion Kalman Filtering Algorithm

Reduced Dimension Measurement Fusion Kalman Filtering Algori...

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2010 Chinese Control and Decision Conference

作者： Yuan Gao,Zili Deng Department of Automation,Heilongjiang University,Harbin 150086,China

For the multisensor systems with the correlated measurement noises and different measurement matrices, based on the linear unbiased minimum variance(LUMV) criterion,a weighted measurement fusion Kalman filtering algorithm is presented,which is identical to that derived by the weighted least squares(WLS) method,and it is numerically identical to the centralized fusion Kalman filtering algorithm,so that it has the global *** optimal weights are given by the Lagrange multiplier *** their computation burden is *** order to reduce the computational burden,another reduced dimension algorithm for computing the optimal weights is derived,which avoids the Lagrange multiplier method,and can significantly reduce the computational *** comparison of the computational counts between two algorithms for computing weights is given.A simulation example shows the effectiveness and correctness of the proposed algorithm.

关键词： Reduced Dimension Algorithm weighted measurement fusion Linear Unbiased Minimum Variance(LUMV) Criterion Lagrange Multiplier Method Kalman Filtering

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WMF full-order Kalman smoother for multisensor Descriptor systems with correlated noises

WMF full-order Kalman smoother for multisensor Descriptor sy...

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第36届中国控制会议

作者： Chenjian Ran Yinfeng Dou Yuan Gao Department of Automation Heilongjiang University

ISBN: (纸本)9781538629185

For the multisensor descriptor systems with correlated noises,the WMF full-order Kalman smoother is ***,the centralized fusion descriptor system is *** this centralized fusion descriptor system is transformed to the descriptor system with uncorrelated ***,the weighted measurement fusion（WMF） descriptor system is ***,the WMF full-order Kalman and smoother and its smoothering error variance are presented,based on the maximum likelihood（ML） estimation and extended state method.A simulation example of a 3-sensor descriptor systems with common distribute noises verifies its effectiveness and the accuracy relation of the presented WMF full-order Kalman smoother.

关键词： multisensor descriptor systems correlated noises weighted measurement fusion full-order Kalman smoother

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