INS/magnetometer integrated positioning based on neural network for bridging long-time GPS outages

In global position system (GPS) and inertial navigation system (INS) integrated navigation systems, the positioning method based on artificial intelligence (AI) learning algorithms has the disadvantage of position diverging as the GPS outages time continues. To solve this problem, INS/magnetometer integrated positioning based on neural network is proposed for bridging GPS outages over a long time. First, the possibility of using magnetometer for positioning is verified by analyzing the international geomagnetic reference field model and the magnetometer measurement model. Then, a magnetometer-assisted positioning solution is proposed. This solution includes four parts: the magnetic fields update module with adaptive extended Kalman filter (AEKF), predictor by AI, INS/GPS integration with KF, and INS/position integration with AEKF. The simulation and driving test results show that the proposed method can keep most of the position errors within a certain range and there is no tendency of divergence at all.