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Optimal Centralized, Recursive, and Distributed Fusion for Stochastic Systems with Coupled Noises

  • Hongbin MaEmail author
  • Liping Yan
  • Yuanqing Xia
  • Mengyin Fu
Chapter

Abstract

In this chapter, optimal state estimation for linear systems is introduced, where the noises of different sensors are cross-correlated and also coupled with the system noise of the previous step. The main result is that the optimal linear estimation is generated in recursive form (Optimal Recursive Fusion: ORF) and distributed fusion (Optimal Distributed Fusion: ODF). They are both compared with the optimal batch fusion (OBF) algorithm by use of many measures, besides the traditional statistical estimation error and the trace of the estimation error covariances, some measures related to the normalized estimation error square or the Mahalanobis distance are introduced and analyzed. Simulation on a target tracking example is done to show the effectiveness of the presented algorithms and to illustrate the usefulness of the novel measure indices.

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Copyright information

© Science Press 2020

Authors and Affiliations

  • Hongbin Ma
    • 1
    Email author
  • Liping Yan
    • 1
  • Yuanqing Xia
    • 1
  • Mengyin Fu
    • 1
  1. 1.School of AutomationBeijing Institute of TechnologyBeijingChina

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