Simulation Research on Gravity-Geomagnetism Combined Aided Underwater Navigation

Gravity Aided Navigation (GravAN) and Geomagnetism Aided Navigation (GeomAN) are two methods for correcting Inertial Navigation System (INS) errors of Autonomous Underwater Vehicles (AUVs) without compromising the AUV mission. One requirement for applying these methods is the relatively large field feature variations along the navigation trajectory. But in some regions with small gravity or geomagnetic variation, it is very difficult to achieve a reliable result solely by GravAN or GeomAN. If these two methods were combined, gravity and geomagnetism information could be complementary and the aided navigation ability could potentially be improved, especially in those regions when neither method is valid. Based on that concept, a Gravity and Geomagnetism Combined Aided Navigation (GGCAN) method is consequently proposed in this paper as a possible solution. The Gravity Anomaly Grid (GAG2) and Earth Geomagnetic Anomaly Grid (EMAG2) are utilized as the background databases, and then a Multiple Model Adaptive Estimation (MMAE) is adopted to obtain an optimal estimated navigation position. Furthermore, an Optimal Weight Allocation Principle (OWAP) is introduced to the combined GravAN and GeomAN methods, together with a weighted average. In simulation, two special regions in the Western Pacific Ocean were chosen to test the proposed method. The results show that GGCAN can improve the position success rate and reduce the error, compared to GravAN or GeomAN. Results indicate that the GGCAN method proposed in this study is able to improve the accuracy and reliability of an aided navigation system.