Fingerprint database4/25/2023 In recent years, received signal strength (RSS) fingerprint-based Wi-Fi positioning methods have attracted the attention of many researchers because RSS can be easily obtained by a Wi-Fi-integrated mobile device without any additional hardware. The rapid development of smartphones has made it a carrier of location-based service (LBS), such as indoor localization, navigation, and tracking. Experiments show that the proposed RSSD-CS algorithm can achieve high localization accuracy in indoor localization, and the accuracy is enhanced by 20.5% and 15.6% compared to SSD and CS algorithm. Besides, a fingerprint database is reconstructed from the existing reference point data. To address this issue, a fusion method based on received signal strength difference and compressive sensing (RSSD-CS) is proposed in this paper, which can reduce the influence caused by the terminal heterogeneity. Therefore, the impact of terminal heterogeneity on localization accuracy can be overlooked. Even for the same signal, RSSI values obtained by different terminals at the same time and the same location may be different. ![]() However, since a uniform standard for measuring components of smartphones has not yet been established, the Wi-Fi chipsets on different smartphones may have different sensitivity levels to different Wi-Fi access points (APs) and channels. Most current localization methods are based on the comparison between the received signal strength indication (RSSI) and the RSS in the database, whose nearest reference point is the location point. With the development of network technology, WLAN-based indoor localization plays an increasingly important role.
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