Abstract

The performance of an inertial navigation system (INS) and global positioning system (GPS) integrated navigation system is reduced during GPS outages. To bridge GPS outages, a fusion methodology to provide pseudo GPS position information is proposed. The methodology consists of two parts, empirical mode decomposition threshold filtering (EMDTF) and a long short-term memory (LSTM) neural network. The EMDTF eliminates the noise in inertial sensors and provides more accurate data for subsequent calculations. The LSTM uses the current specific forces and angular rates to predict the pseudo GPS position during GPS outages. To evaluate the effectiveness of the proposed methodology, numerical simulations and real field tests are employed. Compared with the traditional artificial neural networks, the results illustrate the proposed methodology can significantly improve the navigation accuracy during GPS outages and the model is simpler.

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