Share Email Print
cover

Proceedings Paper

Target classification algorithm based on feature aided tracking
Author(s): Ronghui Zhan; Jun Zhang
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

An effective target classification algorithm based on feature aided tracking (FAT) is proposed, using the length of target (target extent) as the classification information. To implement the algorithm, the Rao-Blackwellised unscented Kalman filter (RBUKF) is used to jointly estimate the kinematic state and target extent; meanwhile the joint probability data association (JPDA) algorithm is exploited to implement multi-target data association aided by target down-range extent. Simulation results under different condition show the presented algorithm is both accurate and robust, and it is suitable for the application of near spaced targets tracking and classification under the environment of dense clutters.

Paper Details

Date Published: 14 March 2013
PDF: 7 pages
Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 87682G (14 March 2013); doi: 10.1117/12.2010883
Show Author Affiliations
Ronghui Zhan, National Univ. of Defense Technology (China)
Jun Zhang, National Univ. of Defense Technology (China)


Published in SPIE Proceedings Vol. 8768:
International Conference on Graphic and Image Processing (ICGIP 2012)
Zeng Zhu, Editor(s)

© SPIE. Terms of Use
Back to Top