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Self-tuning measurement fusion white noise deconvolution estimator with correlated noises

Journal of Systems Engineering and Electronics 2010年第4期21卷 666-674页

作者： Xiaojun Sun Zili Deng Department of Automation Heilongjiang University Harbin 150080 R R. China

For the multisensor linear discrete time-invariant stochastic systems with correlated noises and unknown noise statistics,an on-line noise statistics estimator is presented by using the correlation *** it into the steady-state Riccati equation,the self-tuning Riccati equation is *** the Kalman filtering method,based on the self-tuning Riccati equation,a self-tuning weighted measurement fusion white noise deconvolution estimator is *** the dynamic error system analysis（DESA） method,it is proved that the self-tuning fusion white noise deconvolution estimator converges to the optimal fusion steadystate white noise deconvolution estimator in a realization,so that it has the asymptotic global optimality.A simulation example for Bernoulli-Gaussian input white noise shows its effectiveness.

关键词： multisensor information fusion measurement fusion self-tuning fuser white noise deconvolution asymptotic global optimality Kalman filtering convergence.

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SELF-TUNING WEIGHTED MEASUREMENT FUSION white noise deconvolution ESTIMATOR

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Journal of Electronics(China) 2010年第1期27卷 51-59页

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

For the multi-sensor linear discrete time-invariant stochastic systems with correlated measurement noises and unknown noise statistics,an on-line noise statistics estimator is obtained using the correlation *** it into the optimal weighted fusion steady-state white noise deconvolution estimator based on the Kalman filtering,a self-tuning weighted measurement fusion white noise deconvolution estimator is *** the Dynamic Error System Analysis(DESA) method,it proved that the self-tuning fusion white noise deconvolution estimator converges to the steady-state optimal fusion white noise deconvolution estimator in a ***,it has the asymptotically global optimality.A simulation example for the tracking system with 3 sensors and the Bernoulli-Gaussian input white noise shows its effectiveness.

关键词： Multi-sensor information fusion Self-tuning fuser white noise deconvolution Global optimality Convergence

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维普期刊数据库

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Time-varying optimal distributed fusion white noise deconvolution estimator

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Frontiers of Electrical and Electronic Engineering in China 2012年第3期7卷 318-325页

作者： Xiaojun SUN Guangming YAN College of Electrical Engineering Heilongjiang University Harbin150080 China

white noise deconvolution has a wide range of applications including oil seismic exploration, communication, signal processing, and state estimation. Using the Kalman filtering method, the time-varying optimal dis- tributed fusion white noise deconvolution estimator is presented for the multisensor linear discrete time-varying systems. It is derived from the centralized fusion white noise deconvolution estimator so that it is identical to the centralized fuser, i.e., it has the global optimality. It is superior to the existing distributed fusion white noise estimators in the optimality and the complexity of computation. A Monte Carlo simulation for the Bemoulli- Gaussian input white noise shows the effectiveness of the proposed results.

关键词： multisensor information fusion distributedfusion white noise deconvolution global optimality Kal-man filtering

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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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Self-tuning white noise deconvolution Fuser with Asymptotic Global Optimality

Self-tuning White Noise Deconvolution Fuser with Asymptotic ...

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2010 Chinese Control and Decision Conference

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

＜正＞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 noises and unknown noise statistics,an on-line noise statistics estimator is given by the correlation *** the Kalman filtering method,based on the self-tuning Riccati equation,a self-tuning weighted measurement fusion white noise deconvolution estimator is *** the dynamic error system analysis（DESA） method,it is proved that the self-tuning white noise deconvolution fuser converges to the steady-state optimal white noise deconvolution fuser in a realization so that it has the asymptotic global optimality.A simulation example for a 3-sensor system with Bernoulli-Gaussian input white noise shows its effectiveness.

关键词： Multisensor Information Fusion Weighted Measurement Fusion Self-tuning Fuser white noise deconvolution Global Optimality Kalman Filtering Convergence

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