Course paper / final thesis

Development of a Machine Learning-based Train Odometry Using Magnetic Field Distortions

Starting date

1 April 2023

Duration of contract

6 months


up to German TVöD 5

Type of employment


Climate change and an increasing urbanization requires efficient and CO2 neutral transportation. In principle this can be achieved with rail-bound vehicles but current railway systems suffer from a lack of automation that not only makes them unattractive to costumers but also inefficient in the use of the existing infrastructure. The Vehicular Applications group therefore develops key technologies that enable a higher degree of automation of railway traffic to address the mentioned limitations.

One technology currently developed is a localization system that uses distortions of the Earth magnetic field. This magnetic field-based system works also in areas of the track network in which satellite-based systems are not available, such as tunnels. The magnetic localization system exploits that ferromagnetic material in the track infrastructure introduces position dependent distortions in the Earth magnetic field. A map of these distortions then can be used to localize trains by comparing the measurements of a magnetometer to the map. You will develop an odometry that makes use of the magnetic distortions using methods of machine learning and pattern recognition.

Your qualifications:

  • study of Electrical Engineering, Computer Science or similar
  • hands-on experience with different machine learning methods
  • very good knowledge in MATLAB and Python
  • very good written and spoken knowledge of English or German
  • ability to work independently

Your benefits:

Look forward to a fulfilling job with an employer who appreciates your commitment and supports your personal and professional development. Our unique infrastructure offers you a working environment in which you have unparalleled scope to develop your creative ideas and accomplish your professional objectives. Our human resources policy places great value on a healthy family and work-life-balance as well as equal opportunities for persons of all genders (f/m/x). Individuals with disabilities will be given preferential consideration in the event their qualifications are equivalent to those of other candidates.

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Technical contact

Benjamin Siebler
Institute of Communications and Navigation

Phone: +49 8153 282870

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Vacancy 78302

HR department Oberpfaffenhofen

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DLR site Oberpfaffenhofen

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DLR Institute of Communications and Navigation

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