Design of fingerprinting technique for indoor localization using AM radio signals

As GPS cannot reliably reach and cover any covered area or indoor location, many past studies and research considered the application of Signals of Opportunity (SoOp) such as Wi-Fi, Bluetooth, RFID, Cellular Networks, and FM signals for indoor positioning and object tracking. However, not all SoOp can be part of the indoor positioning experiment due to some limitations; for example, not all signals are cost-effective; some are less accurate in finding position; some require additional hardware for deployment. In this study, a new technique of indoor navigation is introduced exploiting AM radio signals and the received signal strength (RSS) fingerprinting method. This research investigates the fingerprinting technique with the deterministic approach via three algorithms such as Nearest Neighbour (NN), K-Nearest Neighbour (KNN), and K- Weighted Nearest Neighbour (KWNN) for measuring the mean distance error (MDE) as the prime indicator of localization accuracy. The result demonstrates that the Nearest Neighbour algorithm performed best for K=1 and the lowest mean distance error in the ground and the first floor is less than 3m