Information Fusion for Multi-sensor System with Finite-time Correlated Process Noises

  • Fan Li
  • Wujia Zeng
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 241)


When the process noises are finite-time correlated in multi-sensor system for engineering monitoring and management, a systematic way to handle the corresponding distributed estimation fusion problem is proposed in this paper. A distributed fusion algorithm based on Kalman filtering is developed, in which the traditional state estimation method to deal with correlated noises by augmenting the state vector of systems is avoided so as not to increase the dimension of state vector. The proposed distributed estimation fusion algorithm guarantees the optimality in the sense of being equivalent to the optimal centralized estimation fusion. The optimality of the new distributed fusion algorithm in multiple-step correlated process noises cases is also analyzed. Comparisons with the existing distributed estimation fusion algorithms are given to demonstrate the performance of the new algorithm.


Multi-sensor system Estimation fusion Distributed fusion Finitetime correlation 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Uncertain Decision-Making LaboratorySichuan UniversityChengduPeople’s Republic of China
  2. 2.School of EconomicsSichuan UniversityChengduPeople’s Republic of China

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