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A New Diffusion Kalman Algorithm Dealing with Missing Data

  • Shuangyi XiaoEmail author
  • Nankun Mu
  • Feng Chen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11555)

Abstract

In this paper, we propose a novel modified distributed Kalman algorithm, which is a diffusion strategy that the state estimation is more precise while the system model is time-varying. Our focus is on the missing data gathered by a set of sensor nodes that may obtain incomplete information because of the harsh environment. Simulation results evaluate the performance of the proposed distributed Kalman filtering algorithm.

Keywords

Diffusion estimation Kalman filtering Missing data 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.College of Electronic and Information EngineeringSouthwest UniversityChongqingPeople’s Republic of China

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