Nested Preanalyzed and Real-Time Corrected Matching Area Selection Method for Underwater Gravity-Aided Inertial Navigation

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Abstract
Gravity-aided inertial navigation system (GAINS) is an effective passive navigation method, which represents significant progress in underwater navigation. The matching area selection algorithm is one of the key techniques. Distinctive from conventional methods, in this article, a nested method for matching area selection is proposed, which establishes a joint observation of gravity anomalies at the current positions and auxiliary positions to obtain more abundant observational information. Comprehensively considering factors such as sensors, gravity anomaly map, and trajectory, etc., this method measures the matching capacity from a system perspective rather than the 2-D image characteristics, and quantitatively estimates the matching biases. The possible maneuvering navigation and other changes of trajectory and attitude angles are focused on, and a preanalysis and real-time correction method is designed accordingly. Experimental results show that the proposed method can select matching area more accurately and efficiently, and makes it easier to set the matching area selection criteria than conventional algorithms.

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