Abstract:]Indoor positioning by the use of wireless sensor networks is a hot topic for research. The traditional ranging positioning method based on the strength of received signals can not work in complex and dynamic environment because the necessary priori ranging model parameters of the positioning scene can only be obtained through artificial modeling. The current research based on the analysis of ranging models, by attaching different path loss exponents to each reference node through the communication between the reference nodes, achieves the selfadaptation and automation of indoor positioning. The experimental results show that the positioning accuracy is improved with this algorithm compared to the method through single model parameters.