Geomagnetic matching algorithm based on closest contour point and relative position constraint

Abstract

The inertial navigation system (INS) errors are accumulated over time, so the position errors of each sampling point obtained by INS and applied in the geomagnetic matching algorithm are raised with sampling number increased. And the best transformation to describe the real trajectory and indicated trajectory consists of translation, rotation and stretching. Traditional matching algorithms use only translation and rotation, which couldn't estimate the position errors accumulated during the geomagnetic sampling. Considering that the idea of ICCP algorithm is to gradually approach the real trajectory by iterating the closest contour points, a new algorithm based on the closest contour point and the relative position constraint is proposed, which uses the coordination and geomagnetic intensity of the k+1th sampling point to estimate the coordination of kth sampling point. More accurately, the information of k+1th point is used as feedback to determine the weight of the closest contour point and the INS indicated point. The simulation results show that the proposed algorithm can approach the real trajectory very well and has good real - time performance.