Document Type
Article
Publication Date
8-2020
Abstract
This paper explores the through-the-wall inverse scattering problem via machine learning. The reconstruction method seeks to discover the shape, location, and type of hidden objects behind walls, as well as identifying certain material properties of the targets. We simulate RF sources and receivers placed outside the room to generate observation data with objects randomly placed inside the room. We experiment with two types of neural networks and use an 80-20 train-test split for reconstruction and classification.
DOI
10.1016/j.rinam.2020.100106
Source Publication
Results in Applied Mathematics
Recommended Citation
Wood, A., Wood, R., & Charnley, M. (2020). Through-the-wall radar detection using machine learning. Results in Applied Mathematics, 7, 100106. https://doi.org/10.1016/j.rinam.2020.100106
Comments
© 2020 The Authors. This is an Open Access article published by Elsevier and distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. CC BY-NC-ND 4.0
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