Indoor positioning has become highly important because of the failure of GPS in such areas. Many Wireless Local Area Networks (WLAN) indoor localization studies use the fingerprinting technique. In this study, a new positioning system is proposed based on broadcast FM as a signal of opportunity, with significant benefits for indoor positioning. This localization system uses FM signal strength fingerprinting. The deterministic approach of fingerprinting is considered, and several algorithms are compared. The results demonstrate a minimum mean distance error of 2.96m for the K-Weighted Nearest Neighbors (KWNN) algorithm with K=6. The comparison between using fingerprinting for FM and Wi-Fi is also discussed.
Smartphones are linked with individuals and are valuable and yet easily available sources for characterizing users' behavior and activities. User's location is among the characteristics of each individual that can be utilized in the provision of location-based services (LBs) in numerous scenarios such as remote health-care and interactive museums. Mobile phone tracking and positioning techniques approximate the position of a mobile phone and thereby its user, by disclosing the actual coordinate of a mobile phone. Considering the advances in positioning techniques, indoor positioning is still a challenging issue, because the coverage of satellite signals is limited in indoor environments. One of the promising solutions for indoor positioning is fingerprinting in which the signals of some known transmitters are measured in several reference points (RPs). This measured data, which is called dataset is stored and used to train a mathematical
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