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Open AccessArticle

Deep Learning-Based Localization for UWB Systems

1
School of Electrical and Electronics Engineering, Chung-Ang University, Seoul 06974, Korea
2
Department of Information and Communication Engineering, Hanbat National University, Daejeon 305-719, Korea
*
Author to whom correspondence should be addressed.
Electronics 2020, 9(10), 1712; https://doi.org/10.3390/electronics9101712
Received: 20 September 2020 / Revised: 13 October 2020 / Accepted: 14 October 2020 / Published: 18 October 2020
(This article belongs to the Section Microwave and Wireless Communications)
Localization has been extensively studied owing to its huge potential in various areas, such as Internet of Things, 5G, and unmanned aerial vehicle services. Its wide applications include home automation, advanced production automation, and unmanned vehicle control. In this study, we propose a novel localization method that utilizes convolutional neural network (CNN) and ultra-wideband (UWB) signals. A localization problem is converted to a regression problem with the proposed CNN, in which the ranging and positioning phases are integrated. By integrating the ranging and positioning phases, the proposed CNN estimates the location of UWB transmitter directly without any additional step. To integrate both phases of localization, a simple-yet efficient input image generation method is proposed. In the proposed input image generation method, three oversampled two-dimensional input images are generated from the three received UWB signals and they are provided to the designed CNN through the three channels, which are represented by red-, green-, and blue-color channels, respectively. The proposed CNN-based localization system then estimates the location of the UWB transmitter directly using the three-channel image as an input of the CNN. Simulation results verify that the proposed CNN-based localization method outperforms the traditional threshold-based and existing CNN-based methods. Also, it is observed that the proposed method performs well under an asymmetric environment, unlike the existing method. View Full-Text
Keywords: localization; deep learning; convolutional neural network (CNN); ultra-wideband (UWB) system localization; deep learning; convolutional neural network (CNN); ultra-wideband (UWB) system
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Nguyen, D.T.A.; Lee, H.-G.; Jeong, E.-R.; Lee, H.L.; Joung, J. Deep Learning-Based Localization for UWB Systems. Electronics 2020, 9, 1712.

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