Novel Smoothing Approach for Indoor Positioning Bluetooth Networks using RSSI

In recent years, localization and navigation have been important topics in research. The most popular navigation system is an outdoor navigation with GPS. However, there are many impossibilities when trying to perform positioning within indoor environments, with the use of GPS technology. In order to overcome this limitation, this paper has discussed Bluetooth Low Energy technology based localization model. The BLE provides several major forms of parameters linked to location estimation such as RSSI and LQI. In real time applications such as object tracking and distance estimations, continuous receptions of RSSI measurements are needed in order to estimate accurately the position of the object. In adjacent to those considerations, there are some additional constraints to be inspected such as signal attenuation, signal loss, multipath effects, temperature, reflection, a human body and other communication signals. Hence, this research work has examined the RSSI smoothing approaches in order to obtain preferable results. Although there are so many solutions, no RSSI smoothing method has been recognized as a standard method. This paper presents a Feedback filter together with shifting technique at distance domain to reduce fluctuations of the real-time signals. The experimental outcome of this novel approach has shown that the probability of location-based identification is errorless, and it is better than the other existing interference avoidance algorithms.