A parameterized geometric magnetic field calibration method for vehicles with moving masses with applications to underwater gliders

Author Posting. © The Author(s), 2016. This is the author's version of the work. It is posted here by permission of John Wiley & Sons for personal use, not for redistribution. The definitive version was published in Journal of Field Robotics 34 (2017): 209-223, doi:10.1002/rob.21660. The ac...

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Bibliographic Details
Published in:Journal of Field Robotics
Main Authors: Claus, Brian, Bachmayer, Ralf
Format: Report
Language:English
Published: 2016
Subjects:
Online Access:https://hdl.handle.net/1912/8831
Description
Summary:Author Posting. © The Author(s), 2016. This is the author's version of the work. It is posted here by permission of John Wiley & Sons for personal use, not for redistribution. The definitive version was published in Journal of Field Robotics 34 (2017): 209-223, doi:10.1002/rob.21660. The accuracy of magnetic measurements performed by autonomous vehicles is often limited by the presence of moving ferrous masses. This work presents a parameterized ellipsoid eld calibration method for magnetic measurements in the sensor frame. In this manner the ellipsoidal calibration coe cients are dependent on the locations of the moving masses. The parameterized calibration method is evaluated through eld trials with an autonomous underwater glider equipped with a low power precision uxgate sensor. A rst set of eld trials were performed in the East Arm of Bonne Bay, Newfoundland in December of 2013. During these trials a series of calibration pro les with the mass shifting and ballast mecha- nisms at di erent locations were performed before and after the survey portion of the trials. Further trials were performed in the Labrador Sea in July of 2014 with two reduced sets of calibration runs. The nominal ellipsoidal coe cients were extracted using the full set of measurements from a set of calibration pro les and used as the initial conditions for the polynomials which de ne each parameterized coe cient. These polynomials as well as the sensor misalignment matrix were then optimized using a gradient descent solver which minimizes both the total magnetic eld di erence and the vertical magnetic eld variance between the modeled and measured values. Including the vertical eld in this manner allows for convergence in spite of severe limitations on the platform's motion and for computation of the vehicle's magnetic heading. This work was supported by the Natural Sciences and Engineering Research Council (NSERC) through the NSERC Canadian Field Robotics Network (NCFRN), the Research Development Corporation, the Marine Institute ...