This paper presents an extended Kalman filter-based hybrid indoor position estimation technique which is based on integration of fingerprinting and trilateration approach. In this paper, Euclidian distance formula is used for the first time instead of radio propagation model to convert the received signal to distance estimates. This technique combines the features of fingerprinting and trilateration approach in a more simple and robust way. The proposed hybrid technique works in two stages. In the first stage, it uses an online phase of fingerprinting and calculates nearest neighbors (NN) of the target node, while in the second stage it uses trilateration approach to estimate the coordinate without the use of radio propagation model. The distance between calculated NN and detective access points (AP) is estimated using Euclidian distance formula. Thus, distance between NN and APs provides radii for trilateration approach. Therefore, the position estimation accuracy compared to the lateration approach is better. Kalman filter is used to further enhance the accuracy of the estimated position. Simulation and experimental results validate the performance of proposed hybrid technique and improve the accuracy up to 53.64% and 25.58% compared to lateration and fingerprinting approaches, respectively. 1. Introduction Position estimation is the process which calculates object position with reference to some coordinate system. The position of object can be specified as absolute coordinates consisting of (latitude, longitude) and (x, y) coordinates or in a symbolic form such as room number 1 of the 2nd floor or specific location represented by name. Global positioning system (GPS) is the world first position estimation system which was originally developed by the US Department of Defense for military purpose in order to track the movement of enemies [1]. GPS was originally designed for navigation purpose to track the movement of objects from satellites. However, this technology is used for outdoor applications. The signals transmitted from GPS satellites do not penetrate inside the buildings; hence, it is not applicable for indoor environment [2]. In order to provide an alternate solution for indoor environment, the research community is focusing on low-cost and highly accurate indoor position estimation techniques which can be used for indoor environment [3]. The applications of indoor position estimation systems are different from GPS and not limited to navigation or object tracking. Also apart from this, GPS provides an accuracy from 5 to 10 meters, which is
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