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Mathematical Problems in Engineering
Volume 2017 (2017), Article ID 5752870, 9 pages
Research Article

Tracking Maneuvering Group Target with Extension Predicted and Best Model Augmentation Method Adapted

Air and Missile Defense College, Air Force Engineering University, Shaanxi, China

Correspondence should be addressed to Linhai Gan

Received 13 March 2017; Revised 3 June 2017; Accepted 14 June 2017; Published 24 September 2017

Academic Editor: Vladimir Turetsky

Copyright © 2017 Linhai Gan and Gang Wang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The random matrix (RM) method is widely applied for group target tracking. The assumption that the group extension keeps invariant in conventional RM method is not yet valid, as the orientation of the group varies rapidly while it is maneuvering; thus, a new approach with group extension predicted is derived here. To match the group maneuvering, a best model augmentation (BMA) method is introduced. The existing BMA method uses a fixed basic model set, which may lead to a poor performance when it could not ensure basic coverage of true motion modes. Here, a maneuvering group target tracking algorithm is proposed, where the group extension prediction and the BMA adaption are exploited. The performance of the proposed algorithm will be illustrated by simulation.