Abstract
This paper presents a primitive solution with novel scheme and algorithm for Underwater geoMagnetic Navigation (UMN), which now occurs as the hot-point in the research field of navigation. UMN as an independent or supplementary technique can theoretically supply accurate locations for marine vehicles, but in practice there are plenty of restrictions for UMN's application (e.g., geomagnetic daily variation). After analysis of the theoretical model of geomagnetic positioning in the correlation-matching mode from the viewpoint of pattern recognition, this paper proposed an appropriate matching scenario and a combined positioning algorithm for UMN. The subalgorithm of Hausdorff-based Relative Correlation (RC) corresponding to the pattern classification module implements the coarse positioning, and the subalgorithm of Isograms Equidistance-Segmenting theIntersection Lines (IESILs) associated with the module of feature extraction continues the fine positioning. The experiments based on the simulation platform and the real-surveyed data both validate the new algorithm, and its efficiency and accuracy are also discussed. It can be concluded that the work introduced in this paper gives an initial and real validation of UMN's potentiality.
Highlights
The technique of Underwater geoMagnetic Navigation (UMN) [1] recently has become a hot-point in the research area of navigation
This paper presents a primitive solution with novel scheme and algorithm for Underwater geoMagnetic Navigation (UMN), which occurs as the hot-point in the research field of navigation
The experiments based on the simulation platform and the real-surveyed data both validate the new algorithm, and its efficiency and accuracy are discussed
Summary
The technique of Underwater geoMagnetic Navigation (UMN) [1] recently has become a hot-point in the research area of navigation. This trend will develop further with the unreliability of the Global Navigation Satellite System (GNSS) increasing [2], and with the requirements growing in some special conditions (e.g., submarine exploration) [3]. It even has been deduced that only the Geophysical Field of Earth (GFE) referencing methods (UMN is a typical one) can enable Unmanned Underwater Vehicles (UUV) to navigate accurately over large areas [4, 5]. All influences factors causing voyage drift (such as water currents or sonar failure) are taken for granted in a “black-box” in this paper, and UMN as an independent methodology will be explored to supply the accurate positioning information to rectify the whole “blackbox.”
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