International Journal of Advanced Engineering and Technology

International Journal of Advanced Engineering and Technology


International Journal of Advanced Engineering and Technology
International Journal of Advanced Engineering and Technology
Vol. 5, Issue 2 (2021)

Reduced-order distributed fusion with application to object tracking


Vladimir Shin, Vahid Hamdipoor

In this paper, we propose a novel reduced-order track-to-track fusion filter (ROF) for estimating not all state variables, but only those variables that indicate useful information of a target system for control. The ROF algorithm is designed for multisensory continuous-time stochastic systems. Its communication loads and computational complexity are not so complicated due to usage of the reduced-order local Kalman filters. Performance of the ROF and its estimation accuracy using the covariance intersection fusion are demonstrated on a 2D motion model with several GPSs. Comparative analysis of the ROF with the global optimal centralized Kalman filter is presented. Simulation results demonstrate practical effectiveness of the proposed ROF.
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How to cite this article:
Vladimir Shin, Vahid Hamdipoor. Reduced-order distributed fusion with application to object tracking. International Journal of Advanced Engineering and Technology, Volume 5, Issue 2, 2021, Pages 08-11
International Journal of Advanced Engineering and Technology International Journal of Advanced Engineering and Technology