Multi-sensors data and information fusion algorithm for indoor localization

The localization algorithm of based on IMU is one of autonomous localization methods while it possesses the disadvantage of drift error and accumulated error,so this paper proposes a multi-sensors including wearable multi-IMUs and IWSN data and information fusion algorithm for indoor localization.On the one hand,almost all indoor localization algorithms based on IMU use only one IMU while this single-IMU-based algorithm can′t judge the posture of person precisely,one appropriate solution is that we can utilize multi-IMUs to cooperate in localization process,besides,we can fuse position information of multi-IMUs by fuzzy voting scheme.On the other hand,in order to overcome the disadvantage of drift error and accumulate error,combining with IWSN in indoor and fusing the position information calculated by IWSN and multi-IMUs via Kalman Filter algorithm.Experiment results show that the proposed indoor localization algorithm possesses good property in judging posture of person and decreasing drift error and accumulate error comparing with traditional IMU-based indoor localization algorithm.