Author/Authors :
Du,Kai Engineering Institute of Engineering Corps - PLA University of Science and Technology, China , Fang, Xiang Engineering Institute of Engineering Corps - PLA University of Science and Technology, China , Zhang, Wei-ping Engineering Institute of Engineering Corps - PLA University of Science and Technology, China , Ding, Kai Science and Technology on Near- Surface Detection Laboratory, China
Abstract :
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.
