• KIPS Transactions on Computer and Communication Systems
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• v.6 no.9
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• pp.369-376
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• 2017

Recently, an RSSI-based fingerprinting localization technology has been widely used in indoor location-based services. In the conventional fingerprinting method, as many APs as possible are used to increase the accuracy of location estimation. In another study, a part of APs having the strongest RSSI signal intensity are selected and used to reduce the time spent for positioning. However, it does not reflect the influence of RSSI occurred from the changes of the surrounding environments such as human movement or moving obstacles in a real environment. The environmental changes may cause the difference between the predicted RSSI signal strength value and the measured value, and thus occur an unpredictable error in the position estimation. Therefore, in order to mitigate the error caused by environmental factors, it is necessary to select APs suitable for indoor positioning estimation considering the changes in the surrounding environments. In this paper, we propose a method to select stable APs considering the influence of surrounding environments and derive a suitable positioning algorithm. In addition, we compare and analyze the performance of the proposed method with that of the existing AP selection methods through experiments.