Fingerprint Augment Based on Super-Resolution for WiFi Fingerprint Based Indoor Localization
Fingerprint Augment Based on Super-Resolution for WiFi Fingerprint Based Indoor Localization
复制标题
WiFi指纹室内定位中基于超分辨率的指纹增强算法
DOI：
10.1109/jsen.2022.3174600
复制
发表时间：
2022-06-15
影响因子：
4.3
通讯作者：
Zhang, Sihai
中科院分区：
文献类型：
--
作者：
Lan, Tian;Wang, Xianmin;Zhang, Sihai
基于WiFi指纹的室内定位因其定位精度高、设备部署成本低而成为室内定位领域的重点研究方向。增加离线收集的参考点的数量可以提高定位精度，但它会产生过多的离线收集成本。指纹增强是在保证定位精度的同时降低成本的有效解决方案。本文首次提出了一种基于超分辨率的指纹增强框架（FASR），通过指纹数据与指纹图像之间的相互转换，实现了指纹增强与超分辨率的融合。阐述了FASR的处理框架，并给出了FASR中指纹图像转换模块、超分辨率模块和图像指纹转换模块的实现。仿真和真实的数据实验验证了FASR的可行性和有效性。此外，我们探讨了两个关键的工程参数的FASR方法的性能的影响。本文的工作展示了超分辨率技术在图像处理领域的新应用--无线室内定位。
WiFi fingerprint based indoor localization has become a key research direction in the field of indoor localization due to its high positioning accuracy and low equipment deployment cost. Increasing the number of reference point collected offline can improve the positioning accuracy, however it yields excessive cost of offline collection. Fingerprint augment is an effective solution to reduce the cost while ensuring the positioning accuracy. In this paper, we are pioneering to propose a fingerprint augment framework based on super-resolution (FASR), which achieves the fusion of fingerprint augment and super-resolution based on mutual conversion between fingerprint data and fingerprint image. The processing framework of FASR is formulated and the implementation of three modules in FASR are given, including Fingerprint-To-Image Conversion module, Super-Resolution module and Image-To-Fingerprint Conversion module. Simulated and real data experiments reveal the feasibility and effectiveness of the FASR. In addition, we explore the impact of two key engineering parameters on the performance of the FASR method. Our work demonstrates the new application of super-resolution in image processing field in wireless indoor localization topics.