By Topic

Fuzzy-based Error Correction Mechanism to Improve the Precision of Intelligent Maneuvering Target Tracking

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Tsung-ying Sun ; Department of Electrical Engineering, National Dong Hwa University, No. 1, Sec. 2, Da Hsueh Rd. Shoufeng, Hualien, Taiwan, R.O.C. ; Shang-jeng Tsai ; Hung-chun Chen ; Shan-ming Yang

This paper proposes a fuzzy-based error correction mechanism (FECM) to improve the precision of an online data-driven fuzzy clustering (ODDFC) used in the maneuvering target tracking and trajectory prediction. In the ODDFC, the observed data are extracted automatically by fuzzy inference mechanism without much computation and training costs. But the improvement performance of ODDFC is slightly due to its parameters limitation and the prediction accuracy can be affected by the trajectory's curvature of moving target. So we propose ODDFC with FECM to solve the problem. In the proposed method, we use fuzzy inference system that has error correction mechanism to reduce the prediction error of ODDFC. ODDFC with FECM can predict maneuvering targets adapt quickly and have better prediction performance than ODDFC. Simulation results show that proposed method can improve the performance of ODDFC

Published in:

2006 IEEE International Conference on Information Reuse & Integration

Date of Conference:

16-18 Sept. 2006