ARCHIVES
VOL. 5, ISSUE 2 (2021)
Reduced-order distributed fusion with application to object tracking
Authors
Vladimir Shin, Vahid Hamdipoor
Abstract
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.
Download
Pages:08-11
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, Vol 5, Issue 2, 2021, Pages 08-11
Download Author Certificate
Please enter the email address corresponding to this article submission to download your certificate.