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PIER PIER B PIER C PIER M PIER Letters PIER Photonics
2011-04-29
The Support Vector Machine for Dielectric Target Detection through a Wall
By
Fang-Fang Wang,

    Dr. Fang-Fang Wang

    School of Electronics Science and Engineering

    Nanjing University of Posts and Telecommunications

    China

    Homepage

Ye-Rong Zhang

    Dr. Ye-Rong Zhang

    Nanjing University of Posts and Telecommunications

    China

    Homepage

Progress In Electromagnetics Research Letters, Vol. 23, 119-128, 2011
doi:10.2528/PIERL11031106 | Google Scholar

Abstract
In this paper, a novel approach based on the support vector machine (SVM) for dielectric target detection in through-wall scenario is proposed. Through-wall detection is converted to the establishment and use of a mapping between backscattered data and the dielectric parameter of the target. Then the propagation effects caused by walls, such as refraction and speed change, are included in the mapping that can be regressed after SVM training process. The training and testing data for the SVM is obtained by finite-difference time-domain (FDTD) simulation. Numerical experiments show that once the training phase is completed, this technique only needs computational time in an order of seconds to predict the parameters. Besides, experimental results show that good consistency between the actual parameters and estimated ones is achieved. Through-wall target tracking is also discussed and the results are acceptable.
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Citation
Fang-Fang Wang, and Ye-Rong Zhang, "The Support Vector Machine for Dielectric Target Detection through a Wall," Progress In Electromagnetics Research Letters, Vol. 23, 119-128, 2011.
doi:10.2528/PIERL11031106
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