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Journal of Applied Remote Sensing

Real-time through-the-wall radar imaging under unknown wall characteristics using the least-squares support vector machines based method
Author(s): Hua-Mei Zhang; Zheng-Bin Wang; Zhi-Hang Wu; Fang-Fang Wang; Ye-Rong Zhang
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Paper Abstract

To solve the real-time through-the-wall imaging problem in the presence of wall ambiguities, an approach based on the least-squares support vector machines (LS-SVMs) is proposed. This technique converts the through-the-wall problem into the establishment and use of a mapping between the backscattered data and the target properties. The wall parameters and the propagation effects caused by the walls are both included in the mapping and can be regressed after the LS-SVM training process. The target properties are estimated using LS-SVM. Noiseless and noisy measurements are performed to demonstrate that the approach can provide comparable performance in terms of robustness and efficacy, as well as improved performance in terms of accuracy and convenience, in comparison with the approach based on the support vector machine (SVM). The influence of the radius of the target on the estimation problem is discussed, and the estimated results show that both the LS-SVM and the SVM have good performances in terms of generalization.

Paper Details

Date Published: 25 April 2016
PDF: 8 pages
J. Appl. Remote Sens. 10(2) 020501 doi: 10.1117/1.JRS.10.020501
Published in: Journal of Applied Remote Sensing Volume 10, Issue 2
Show Author Affiliations
Hua-Mei Zhang, Nanjing Univ. of Posts and Telecommunications (China)
Zheng-Bin Wang, Nanjing Univ. of Posts and Telecommunications (China)
Southeast Univ. (China)
Zhi-Hang Wu, Nanjing Univ. of Posts and Telecommunications (China)
Fang-Fang Wang, Nanjing Univ. of Posts and Telecommunications (China)
Ye-Rong Zhang, Nanjing Univ. of Posts and Telecommunications (China)


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