ANALYZING THE PERFORMANCE OF PURE LATERATION IN INDOOR ENVIRONMENTS WITH VARIOUS PERFORMANCE METRICS

Nowadays, determining the location of the users and devices in indoor buildings is promising research topic. Accurate position determination of the users for indoor environments is used for numerous applications such as public safety, supermarkets, health care applications, travelling, social networks and tourism. However, global positioning systems created for outdoor localizations cannot be used for indoor positioning systems (IPS) because detecting the exact position of a target is an issue for IPS. For indoor environments, there are several positioning algorithms such as lateration, fingerprinting, dead reckoning etc. Lateration is low cost and easy to deploy when compared to other existing algorithms. Therefore, in this study, received signal strength based pure lateration that uses synthetic data generated from MATLAB is proposed. The performance of pure lateration is investigated in terms of several performance metrics such as effect of varying number of the access points (AP), varying dimensions of the measurement area, varying Gaussian Noise power and varying number of test points in the field. The simulation of the pure lateration algorithm is conducted in MATLAB. The effect of the performance metrics are investigated and discussed in details. According to the results, accuracy performance of lateration is increased when the number of APs increase in the area, however this will bring some hardware costs. In addition, when the number of test points increases in the field, in other words the step size between two test points decreases in the field the error performance of lateration is also enhanced however, this will also cause to computational costs. Finally, enlarging the measurement area causes to decrease the accuracy performance of lateration as expected. The main purpose of this study is to obtain the optimum conditions for lateration to provide a solution for real time applications. For future work, the real time implementations of this study are performed and to improve the accuracy performance, it is aimed to use a curve fitting idea to the measured values.