An adaptive ranging model under changeable environment

Abstract

Due to the complexity of the indoor environment, this paper proposes an adaptive ranging T-S model (ADRTS). The new model can be through self-learning to range and improve the ranging accuracy. The proposed method exploits the adaptive to range precisely under the changeable environments. Compared with the classical ranging model, the proposed model is with high accuracy under the indoor environment about localization, and it is feasible and simple. In the indoor environment, the simulation experiment indicates that this method is feasible and effective for improving ranging accuracy and will help to improve the accuracy of localization of node.