Abstract
This paper deals with the calibration of a magnetic digital compass for measuring the heading angle of a vessel. The main source of error in the heading measurement is the distortion caused by the presence of ferrous materials nearby the instrument that produces a local magnetic field interfering with the earth magnetic field. This distortion generally changes as the vessel moves around and, for this reason, it is generally difficult to compensate. Tuning the calibration algorithm based on data collected dynamically rather than at a fix location, as it is the standard practice, allows to account for this time-varying characteristics, while avoiding at the same time to discontinue the vessel operation. The accuracy achieved by different calibration algorithms tuned on data collected on a car ferry performing a round trip in the Venetian lagoon is analysed. In particular, a calibration algorithm combining the elliptical model of the magnetic distortion with a neural network is proposed.
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