NDLI: Wavelet Feature Outdoor Fingerprint Localization Based on ResNet and Deep Convolution GAN

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Wavelet Feature Outdoor Fingerprint Localization Based on ResNet and Deep Convolution GAN

Content Provider	MDPI
Author	Lei, Yingke Li, Da Zhang, Haichuan Li, Xin
Copyright Year	2020
Description	Due to the explosive development of location-based services (LBS), localization has attracted significant research attention over the past decade. Among the associated techniques, wireless fingerprint positioning has garnered much interest due to its compatibility with existing hardware. At present, with the widespread deployment of long-term evolution (LTE) networks and the uniqueness of wireless information fingerprints, fingerprint positioning based on LTE networks is the mainstream method for outdoor positioning. However, in order to improve its accuracy, this method needs to collect enough data at a large number of reference points, which is a labor-intensive task. In this paper, experimental data are collected at different reference points and then converted into wavelet feature maps. Then, a Deep Convolutional Generative Adversarial Network (DCGAN) is leveraged to generate a symmetric fingerprint database. Localization is then carried out by the proposed Deep Residual Network (Resnet), which is capable of learning reliable features from a fingerprint image database. To further increase the robustness of the positioning system, a variety of data enhancement methods are used. Finally, we experimentally demonstrate that the generated symmetric fingerprint database and proposed Resnet reduce the manpower required for fingerprint database collection and improve the accuracy of the outdoor positioning system.
Starting Page	1565
e-ISSN	20738994
DOI	10.3390/sym12091565
Journal	Symmetry
Issue Number	9
Volume Number	12
Language	English
Publisher	MDPI
Publisher Date	2020-09-22
Access Restriction	Open
Subject Keyword	Symmetry Industrial Engineering Transportation Science and Technology Fingerprint Positioning Deep Learning Outdoor Positioning Wavelet Transform
Content Type	Text
Resource Type	Article

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