Improving the Reliability of Underwater Gravity Matching Navigation Based on a Priori Recursive Iterative Least Squares Mismatching Correction Method

This study focuses on the reliability of underwater gravity matching navigation. Firstly, the research started with the post-processing of mismatching. Under the guidance of priori recursive multiple matching and iterative least squares, a new priori recursive iterative least squares mismatching correction (PRILSMC) method was proposed based on statistics and the fitting principle. Secondly, according to factors such as matching algorithm probability, error of INS, and the actual situation, we comprehensively considered the effects of recursive sampling points, priori matching points, etc. The new mismatching judgment and dynamic correction (MJDC) model was constructed based on the PRILSMC method. Finally, under the same conditions, the MJDC model was used to verify a new matching point in three matching regions. The results showed that in the excellent-suitability region, the matching probability increased from about 96% to 100%, i.e., all mismatching points could essentially be eliminated. In the general-suitability region, the matching probability increased from about 64% to 92%, indicating that the probability of mismatching point was greatly reduced, and the reliability of the matching navigation was improved.