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PIER PIER B PIER C PIER M PIER Letters
2012-11-03
Sparse Time-Frequency Representation Based Feature Extraction Method for Landmine Discrimination
By
Yuming Wang,

    Dr. Yuming Wang

    School of Electronic Science and Engineering

    National University of Defense Technology

    China

    Homepage

Qian Song,

    Dr. Qian Song

    School of Electronic Science and Engineering

    National University of Defense Technology

    China

    Homepage

Tian Jin,

    Dr. Tian Jin

    School of Electronic Science and Engineering

    National University of Defense Technology

    China

    Homepage

Yunfei Shi,

    Dr. Yunfei Shi

    School of Electronic Science and Engineering

    National University of Defense Technology

    China

    Homepage

Xiao-Tao Huang

    Dr. Xiao-Tao Huang

    College of Electronic Science and Engineering

    National University of Defense Technology

    China

    Homepage

Progress In Electromagnetics Research, Vol. 133, 459-475, 2013
doi:10.2528/PIER12082104
Abstract
Low-frequency ultra-wideband synthetic aperture radar is a promising technology for landmine detection. According to the scattering characteristics of body-of-revolution (BOR) along with azimuth angles, a discriminator based on Bayesian decision rule is proposed, which uses sequential features, i.e. double-hump distance. First, the algorithm estimates the target scatterings in all azimuth angles based on regions of interest. Second, sequential aspect features are extracted by sparse time-frequency representation. Third, the distributions of features are obtained by training samples, and then the posterior probability of landmine class is computed as an input to the classifier adopting Mahalanobis distance. The experimental results indicate that the proposed algorithm is effective in BOR target discrimination.
Citation
Yuming Wang, Qian Song, Tian Jin, Yunfei Shi, and Xiao-Tao Huang, "Sparse Time-Frequency Representation Based Feature Extraction Method for Landmine Discrimination," Progress In Electromagnetics Research, Vol. 133, 459-475, 2013.
doi:10.2528/PIER12082104
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