Closed-loop estimation for randomly sampled measurements in target tracking system
type: Item
instance of: scholarly article
title: Closed-loop estimation for randomly sampled measurements in target tracking system
zbMATH Open document ID: 1407.93371
DOI: 10.1155/2014/315908
author: Xue-bo Jin
author: Xiao-feng Lian
author: Tingli Su
author: Yan Shi
author: Bei-bei Miao
published in: Mathematical Problems in Engineering
publication date: 2019-02-08T00:00:00Z
review text: Summary: Many tracking applications need to deal with the randomly sampled measurements, for which the traditional recursive estimation method may fail. Moreover, getting the accurate dynamic model of the target becomes more difficult. Therefore, it is necessary to update the dynamic model with the real-time information of the tracking system. This paper provides a solution for the target tracking system with randomly sampling measurement. Here, the irregular sampling interval is transformed to a time-varying parameter by calculating the matrix exponential, and the dynamic parameter is estimated by the online estimated state with Yule-Walker method, which is called the closed-loop estimation. The convergence condition of the closed-loop estimation is proved. Simulations and experiments show that the closed-loop estimation method can obtain good estimation performance, even with very high irregular rate of sampling interval, and the developed model has a strong advantage for the long trajectory tracking comparing the other models.
Mathematics Subject Classification ID: 93E10
Mathematics Subject Classification ID: 93C55
zbMATH DE Number: 7016152
Wikidata QID: Q59065804
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2014/315908
OpenAlex ID: W2077188078
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description: scientific article; zbMATH DE number 7016152