Portable Unmanned Aerial Vehicles (PUAVs) present an enormous application potential, and the real time accurate position and attitude information is the basis of autonomous flight of PUAVs. In order to obtain comprehensive and accurate position and attitude data of PUAVs in flight, focusing on the common sensors configuration of PUAVs, each type of sensor’s characteristic is analyzed, and the data fusion problem of SINS/GPS/Compass combination is presented and studied in this paper. Firstly, the error expressions of MEMS inertia sensors, attitude, velocity and position are researched and derived, and the state equation and observation equation are built, and the discrete equations are derived for computer implementation, so the data fusion model for Kalman Filter fusion algorithms is presented. Then, the data fusion system and algorithms are implemented in software, and the flight data obtained in flight experiment is fed to the software for data fusion. The comparison between original data and fusional data shows that SINS/GPS/Compass data fusion system can promote accuracy of position and attitude markedly.