Particle Filter Method for a Centralized Multisensor System

  • Wei Xiong
  • You He
  • Jing-wei Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3930)


Multisensor state estimation is an important issue in multisensor data fusion. In order to solve the centralized multisensor state estimation problem of a non-Gaussian nonlinear system, the paper proposes a new multisensor sequential particle filter (MSPF). First, the general theoretical model of a centralized multisensor particle filter is obtained. Then, a sequential resampling method is proposed according to the characteristics of a centralized multisensor system. Last, a Monte Carlo simulation is used to analyze the performance of the method. The results of the simulation show that the new method can greatly improve the state estimation precision of a multisensor system. Moreover, it will gain more accuracy in estimation with an increase in sensor numbers.


Particle Filter Sensor Number Nonlinear Filter State Estimation Problem Multisensor System 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Wei Xiong
    • 1
  • You He
    • 1
  • Jing-wei Zhang
    • 1
  1. 1.Research Institute of Information FusionNaval Aeronautical Engineering InstituteYantaiChina

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