Navigation information fusion for an AUV in rivers

Abstract

Autonomous Underwater Vehicles (AUVs) present an enormous application potential, and the real time accurate position and attitude information is important for AUVs. In order to obtain comprehensive and accurate position and attitude data of AUVs, focusing on the common low cost sensors configuration, the data fusion problem of SINS/USBL/AHRS combination is presented and studied in this paper. Firstly, the error expressions of MEMS are researched and derived, and the data fusion model for Kalman Filter fusion algorithms is presented. The method is validated using a data set gathered for a Huangpu river inspection task. The comparison between original data and fusional data shows that SINS/USBL/AHRS data fusion system can promote accuracy of position and attitude markedly.