Integration Matching Algorithm on Gravity Aided Underwater Navigation

Abstract

Marine gravity aided INS navigation, in which Gravity anomaly and gravity gradient of earth gravity field from sensors sensitive to gravity have been supplementary information aided to correct positioning error accumulated with time to achieve precise navigation and graphic trace, has been a fervent and frontier issue in underwater passive navigation technology in application to Autonomous Underwater Vehicle (AUV). Core theoretical technology of gravity aided INS navigation was matching algorithm, in which Terrain Contour Matching (TERCOM), Sandia Inertial Terrain Aided Navigation (SITAN) and Iterative Closest Contour Point (ICCP) were three typical representatives based on gravity reference map. However, these algorithms more or less had some limitations in certain conditions such as a relatively larger INS positioning error. Aiming at the application limitation that positioning error from INS were commonly large when after a long voyage AUVs entered into the region in which gravity could be used to matching, above three algorithms were integrated to use on base of expounding their algorithm models, computation progress and advantages and disadvantages analysis, then integration theory, algorithm design and model foundation were presented to meet practice application demand better.