Indoor Positioning Based on FM Signals and Wi-Fi Signals

With increasing user demands on Location-based Services (LBS) and Social Networking Services (SNS), indoor positioning has become more crucial. Because of the general failure of GPS indoors, non-GNSS navigation technologies are essential for such areas. Utilizing signals of opportunity is a promising alternative navigation method providing adequate geo-location. Wireless Local Area Networks (WLAN) have been used for localisation indoors. In this study, however, a new positioning system is proposed based on another signal of opportunity: broadcast FM. This analogue audio signal has some advantages for indoor positioning purposes over Wi-Fi signals, such as the ability to be received both indoors and outdoors, dense coverage, availability, low-cost and low-power hardware, and high received signal power. In this paper, along with comparing FM and Wi-Fi positioning systems, we increase position accuracy by fusing both methods. The indoor localisation system suggested here utilises the fingerprinting technique based on FM received signal strength. The fingerprinting implementation involves two stages, the training stage and the positioning stage. The matching algorithms used in the fingerprinting method in this work are Nearest Neighbour (NN), K-Nearest Neighbours (KWNN), and the K-Weighted Nearest Neighbours (KWNN). The proposed localisation was tested experimentally. The mean distance error (MDE) is about 3m when the

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