Improving Matching Efficiency and Out-of-domain Reliability of Underwater Gravity Matching Navigation Based on a Novel Soft-margin Local Semicircular-domain Re-searching Model

This paper mainly studies the improvement of the efficiency and out-of-domain reliability of gravity matching navigation for underwater vehicles. To overcome the traversal low-efficiency problem of the traditional terrain contour matching (TERCOM) algorithm and improve the positioning reliability of its out-of-domain mismatches, a novel soft-margin local semicircular-domain re-searching model (SLSR) is proposed by integrating the soft-margin circular grid matching (SCGM) mechanism and the local semicircular grid re-matching (LSGR) mechanism. SCGM uses three times the inertial navigation cumulative error and adds the unit grid resolution as the soft margin boundary to generate the soft-margin circular domain, which contributes to reducing in-domain matching grid points and enhancing the matching efficiency of algorithms. Then the optimal matching position in this soft-margin circular domain is obtained by using the optimization principle of matching indices. LSGR is triggered when the optimal matching position of SCGM is located near the soft-margin circular-domain boundary. It employs this optimal matching point as the center and the unit inertial navigation error as the radius to recreate the semicircular local re-searching matched grid domain (termed as semicircular domain). Moreover, the optimal matching point in this semicircular domain is obtained by the matching index optimization principle, and then it is compared and updated to obtain the final best matching position of SLSR. The simulation results show that SCGM and LSGR of the proposed SLSR method can effectively improve the matching efficiency and out-of-domain matching reliability of underwater navigation, respectively. Under the same testing conditions for the tracking starting points from three gravity regions, the number of out-of-domain mismatches of SLSR, compared with TERCOM, are lower up to 92.68%, 90.24% and 98.62%, while the average matching accuracies are relatively improved by 88.37%, 85.48% and 83.66%, which verifies the validity and feasibility of the proposed SLSR model on improving the efficiency and out-of-domain reliability of underwater gravity matching navigation.