[01] Yonghao Zhao, School of Computer Science and Technology, Nanjing University of Technology, Nanjing, China; School of Information Engineering, Yancheng Teachers University, Yancheng, China.

In recent years, people are increasingly pursuing convenient and networked lifestyles. Therefore, the demand for accurate indoor positioning services is growing continuously. And indoor positioning technology has already become a research hotspot of scholars at home and abroad. Due to the lack of satellite signals in the indoor environment, such as GPS, Beidou and other satellite navigation systems can not be used, indoor positioning needs to find other ways. Meanwhile, with the rapid development and application of Internet of Things technology, numerous indoor positioning methods have emerged. Among these methods, the positioning method based on wireless local area network (WLAN) is one of the more commonly used methods due to the wide coverage of wireless infrastructure and the advantages of simple deployment, low cost and high universality of WiFi. Aiming at the problem that the received signal strength of indoor WiFi is easily affected by indoor environment and multipath effect, thus the connection between location fingerprint and real location is inevitably affected, this paper proposes an improved algorithm based on fuzzy location. This paper focuses on the construction of fingerprint database and fingerprint matching for WiFi fingerprint positioning, summarizes the key technologies of existing WiFi fingerprint positioning, analyzes the challenges in WiFi fingerprint positioning such as the spatial ambiguity and temporal instability of Received Signal Strength (RSS). On this basis, the improved algorithm is tested, and the results show that the algorithm improves the positioning accuracy to a certain extent.

Indoor Localization, Location Fingerprint, Received Signal Strength, Fuzzy Localization

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