Abstract
In this paper, a geomagnetic matching navigation method that utilizes the geomagnetic vector is developed, which can greatly improve the matching probability and positioning precision, even when the geomagnetic entropy information in the matching region is small or the geomagnetic contour line’s variety is obscure. The vector iterative closest contour point (VICCP) algorithm that is proposed here has better adaptability with the positioning error characteristics of the inertial navigation system (INS), where the rigid transformation in ordinary ICCP is replaced with affine transformation. In a subsequent step, a geomagnetic vector information fusion algorithm based on Bayesian statistical analysis is introduced into VICCP to improve matching performance further. Simulations based on the actual geomagnetic reference map have been performed for the validation of the proposed algorithm.
Highlights
Geomagnetic matching is a key aiding navigation technology that can rectify the indication trace of the Inertial Navigation System (INS) by comparing the geomagnetic profile acquired on board with the stored geomagnetic map, which is an ideal autonomous navigation candidate for long range
There is a kind of scalar matching method often used [3,4,5,6,7,8,9,10,11], which minimizes the square of the differences between the norms of magnetometer outputs and the magnitude of stored geomagnetic reference field in correcting the indication trace
Correlation Matching (CM) based algorithm usually lead to the local optimum solutions, depending on the geomagnetic entropy in the matching region and the matching probability and positioning precision will reduce a lot
Summary
Geomagnetic matching is a key aiding navigation technology that can rectify the indication trace of the Inertial Navigation System (INS) by comparing the geomagnetic profile acquired on board with the stored geomagnetic map, which is an ideal autonomous navigation candidate for long range. There is a kind of scalar matching method often used [3,4,5,6,7,8,9,10,11], which minimizes the square of the differences between the norms of magnetometer outputs and the magnitude of stored geomagnetic reference field in correcting the indication trace. Those methods convert the matching problem into a state estimation problem by using datasets collected in the candidate matching region, most of which are not feasible for long time and long range application because the selection of matching region along the expected trace with high adaptability is difficult, and the estimated algorithm might diverge because of insignificant geomagnetic characteristics [3]. We will present the simulation results for the validation of the proposed algorithms
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