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Shock and Vibration
Volume 2016, Article ID 4548365, 5 pages
Research Article

Fractal Dimension Based on Morphological Covering for Ground Target Classification

1Engineering Institute of Engineering Corps, PLA University of Science and Technology, Nanjing 210007, China
2Science and Technology on Near-Surface Detection Laboratory, Wuxi 214000, China

Received 4 November 2015; Accepted 12 January 2016

Academic Editor: Giorgio Dalpiaz

Copyright © 2016 Kai Du et al. 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.


Seismic waves are widely used in ground target classification due to its inherent characteristics. However, they are often affected by extraneous factors and have been found to demonstrate a complicated nonlinear characteristic. The traditional signal analysis methods cannot effectively extract the nonlinear features. Motivated by this fact, this paper applies the fractal dimension (FD) based on morphological covering (MC) method to extract features of the seismic signals for ground targets classification. With the data measured from test field, three different schemes based on MC method are employed to classify tracked vehicle and wheeled vehicle in different operation conditions. Experiment results demonstrate that the three proposed methods achieve more than 90% accuracy for vehicle classification.