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Mathematical Problems in Engineering
Volume 2014, Article ID 315908, 12 pages
Research Article

Closed-Loop Estimation for Randomly Sampled Measurements in Target Tracking System

College of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China

Received 24 October 2013; Revised 30 December 2013; Accepted 30 December 2013; Published 26 February 2014

Academic Editor: Hamid Reza Karimi

Copyright © 2014 Jin Xue-bo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.