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SCIENCE CHINA Information Sciences, Volume 59, Issue 9: 092207(2016) https://doi.org/10.1007/s11432-015-5489-1

Gaussian approximate filter for stochastic dynamic systems with randomly delayed measurements and colored measurement noises

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  • ReceivedJul 23, 2015
  • AcceptedSep 22, 2015
  • PublishedAug 23, 2016

Abstract

In this paper, a new Gaussian approximate (GA) filter for stochastic dynamic systems with both one-step randomly delayed measurements and colored measurement noises is presented. For linear systems, a Kalman filter can be obtained to include one-step randomly delayed measurements and colored measurement noises. On the other hand, for nonlinear stochastic dynamic systems, different GA filters can be developed which exploit numerical methods to compute Gaussian weighted integrals involved in the proposed Bayesian solution. Existing GA filter with one-step randomly delayed measurements and existing GA filter with colored measurement noises are special cases of the proposed GA filter. The efficiency and superiority of the proposed method are illustrated in a numerical example concerning a target tracking problem.


Funded by

National Natural Science Foundation of China(61201409)

National Natural Science Foundation of China(61371173)

China Postdoctoral Science Foundation(2013M530147)

China Postdoctoral Science Foundation(2014T70309)

Heilongjiang Postdoctoral Fund(LBH-Z13052)

Heilongjiang Postdoctoral Fund(LBH-TZ0505)

Fundamental Research Funds for the Central Universities of Harbin Engineering University(HEUCFQ20150407)


Acknowledgment

Acknowledgments

This work was supported by National Natural Science Foundation of China (Grant Nos. 61201409, 61371173), China Postdoctoral Science Foundation (Grant Nos. 2013M530147, 2014T70309), Heilongjiang Postdoctoral Fund (Grant Nos. LBH-Z13052, LBH-TZ0505), and Fundamental Research Funds for the Central Universities of Harbin Engineering University (Grant No. HEUCFQ20150407).


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