Modeling Local Gravity Anomaly Self-Adaption Quotient Reference Maps for Underwater Autonomous Navigation

Gravity navigation, with its independent, passive, concealment and all weather, has become one of the best options of aided inertial navigation system (INS). Precise local gravity or gravity anomaly reference maps will greatly improve the accuracy of autonomous underwater vehicles (AUVs) navigation. Due to the lack of measured gravity data, the previous methods generally used digital elevation model (DEM) to model gravity anomaly reference maps, however, which neglected the impact of terrain density in homogeneity. In this paper, a novel and practical method is proposed for modeling a reference map which takes a full consideration of the terrain density difference. Experimental results show that the proposed method performs better than the existing methods.

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