Abstract

Localization is an important requirement in wireless sensor networks to determine the position of the object. Localization based on RSSI (Received Signal Strength Indicator) has low accuracy is caused by attenuation of the transmitted signal as a function of the distance between nodes. In indoor environment, the PLE (path loss exponent) values are varied depend on the environment characteristic. This value is required to estimate the distance among nodes and it obtained from the measurement process. However, the fluctuation of PLE value based on RSSI is strongly influencing the output of estimation distance. In this paper we propose a cluster-based PLE areas measurement procedure for indoor mobile cooperation localization. The variation values of PLE can be used to calculate distance estimation from RSSI data of mobile object based on nearest distance from anchor node in cooperative localization. The simulation result shows that cluster-based PLE measurement values have capability in decreasing MSE localization up to 16.16 %, meanwhile without clustering the observation area the MSE localization has 32.39 % decreased. The improvement of PLE value on cluster-based area using linear regression yields 18.06 % of MSE localization.

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