Close category search window
 

Multi-radar tracking based on weighted k-means clustering fusion

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
$31 $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)
Yi Zhang ; Res. Center of Intell. Syst. & Robot., Chongqing Univ. of Posts & Telecommun., Chongqing ; Hongchang Liu ; Wenyong Fu ; Haowen Deng

The application of data fusion technology is a research focus in the field of radar tracking. In this paper, weighted k-means clustering method is applied to distinguish the measurements data set of different objectives. Then, the measurements in the different cluster are fused by using kalman filter. The experiment shows that filtering track with k-means clustering fusion is closer to the real track than without clustering.

Published in:
Granular Computing, 2008. GrC 2008. IEEE International Conference on

Date of Conference: 26-28 Aug. 2008

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.