Print Email Facebook Twitter Magnetic Signature Translation for Magnetic Ranging with Drones Title Magnetic Signature Translation for Magnetic Ranging with Drones Author Analikwu, Brendan (TU Delft Electrical Engineering, Mathematics and Computer Science; TU Delft Applied Sciences) Contributor Vijn, A.R.P.J. (mentor) van Dijk, N.H. (mentor) Lepelaars, Eugene (mentor) Heemink, A.W. (graduation committee) Bouwman, W.G. (graduation committee) van Gijzen, M.B. (graduation committee) Degree granting institution Delft University of Technology Programme Applied Mathematics | Applied Physics Date 2020-08-26 Abstract In this thesis, an algorithm to model the magnetic perturbation field caused by ships is designed and implemented. A systematic description of methods used for modelling the magnetic signature of ships is given. The algorithm fits coefficients of a prolate spheroidal harmonic expansion of the scalar potential of the magnetic field using a least angle regression method (LARS) modified to implement Lasso regularisation. A Monte Carlo method with model selection based on Akaike's information criterion (AIC) is used to select optimal parameters specifying the prolate spheroidal coordinate system centred on the ship. Furthermore, a method to restrict the degree and order of the harmonic expansion is presented and an extension of the scikit-learn module in Python is given. The predictive power of the model was verified using simulated test data, which showed that the designed model is able to make adequate predictions, but improvements are needed. Different analyses on the inputs of the model showed that the model is succesful for low levels of noise, but is susceptible to overfitting for higher levels of noise. Several recommendations for further research are made. Subject Magnetic rangingMagnetic multipole expansionLeast angle regressionAkaike's information criterionMagnetic signature To reference this document use: http://resolver.tudelft.nl/uuid:c4bff32e-b89c-4011-8fa7-13c78a85e500 Part of collection Student theses Document type bachelor thesis Rights © 2020 Brendan Analikwu Files PDF Bachelor_Eindproject_Bren ... alikwu.pdf 5.19 MB Close viewer /islandora/object/uuid:c4bff32e-b89c-4011-8fa7-13c78a85e500/datastream/OBJ/view