Remote Estimation with Sensor Scheduling

  • Authors:

  • Li Xiao;Zigang Sun;Desen Zhu;Mianyun Chen

  • Affiliations:

  • Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Department of Control science and Engineering, Huazhong University of Science and Technology, Wuhan, China 4300 ...;Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Department of Control science and Engineering, Huazhong University of Science and Technology, Wuhan, China 4300 ...;Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Department of Control science and Engineering, Huazhong University of Science and Technology, Wuhan, China 4300 ...;Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Department of Control science and Engineering, Huazhong University of Science and Technology, Wuhan, China 4300 ...

  • Venue:
  • ISNN 2009 Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III
  • Year:
  • 2009

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Abstract

A time-varying Kalman filter is proposed to solve the problem of remote estimation with sensor scheduling and measurement loss. The statistical properties of the estimation error are studied. The expectation of the estimation error covariance is proved to have upper and lower bounds. Convergence conditions and methods to calculate these bounds are also presented. The optimal sensor selection probability is found by using gradient search method. When the remote estimator schedules the transmission of sensors using optimal probability, the best estimation performance can be obtained. The validity of the proposed results are demonstrated by numerical examples.