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Distributed Ellipsoidal Intersection Fusion Estimation for Multi-Sensor Complex Systems.

Peng Zhang1,2, Shuyu Zhou1,2, Peng Liu2,3

  • 1School of Instrumentation and Electronic, North University of China, Taiyuan 030051, China.

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|June 10, 2022
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Summary
This summary is machine-generated.

This study introduces a novel distributed ellipsoidal intersection (DEI) fusion estimation method for complex multi-sensor systems. The DEI method effectively handles unknown disturbances and data delays, outperforming other fusion techniques.

Keywords:
data fusionmeasure propagation delayunknown correlationunknown input interference

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Area of Science:

  • Control Systems Engineering
  • Signal Processing
  • Estimation Theory

Background:

  • Multi-sensor systems face challenges with unknown input disturbances and data transmission delays.
  • Accurate state estimation is crucial for complex, time-varying systems.

Purpose of the Study:

  • To develop a robust distributed estimation method for linear time-varying multi-sensor systems.
  • To address unknown input disturbances and measurement data transmission delays.
  • To improve fusion estimation accuracy and computational efficiency.

Main Methods:

  • Utilized a non-informative prior distribution for unknown input disturbances.
  • Modeled data transmission delays using Bernoulli distributed random variables and buffer areas.
  • Designed a Minimum Mean Square Error (MMSE) local estimator within a Bayesian framework (MAP criterion).
  • Employed Ellipsoidal Intersection (EI) fusion for low computational complexity and handling unknown local estimator correlations.

Main Results:

  • Demonstrated the consistency of the developed EI fusion estimator.
  • Showcased the superiority of the DEI fusion method over Distributed Covariance Intersection (DCI) and centralized fusion through a numerical example.
  • Successfully integrated methods to handle system uncertainties and network-induced delays.

Conclusions:

  • The proposed DEI fusion estimation technique offers a superior approach for complex multi-sensor systems.
  • The method effectively mitigates the impact of unknown disturbances and data transmission delays.
  • DEI fusion provides a computationally efficient and consistent estimation solution.