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Course paper / final thesis

Pedestrian Navigation based on Magnetic Field

Starting date

1 May 2021

Duration of contract

6 months


up to German TVöD 5

Type of employment


The position estimation of vulnerable road users like pedestrians, bikers or even cars is broadly investigated and different solutions exists in the literature. Positioning in urban canyons and underground environments like tunnels or station areas where GNSS reception is difficult will require a combination of sensors and other information such as maps of the environment in order to function accurately. We are pursuing sensor fusion approaches that combine GNSS, inertial sensors, and different kinds of maps. A particularly powerful combination for pedestrian navigation is INS (Inertial Navigation System) step measurement in conjunction with GNSS, when GNSS is available. We have developed pedestrian navigation systems with a sensor placed either on the foot or inside the pocket, where the remaining drift can be corrected by different techniques like learning a map of the environment (SLAM), feature detection or GNSS, when available. With these techniques accurate tracks of pedestrians can be calculated in most cases, but the accuracy is still degraded e.g. indoors and in underground areas. In order to function more properly positioning based additionally on a magnetic field map shall be investigated indoors and in an underground station area. Due to build-in ferro-magnetic materials indoors and in underground areas the earth magnetic field is disturbed and a signature of the magnetic field intensity can be measured. The overall goal is to track pedestrians in all kind of environments with the aid of the magnetic field map in order to provide an accurate and reliable position estimate.

Your task is to generate a magnetic map of an indoor and an underground station area with the aid of an existing SLAM algorithm and/or a magnetic field scanner in order to enhance positioning. The main goal is to investigate different positioning techniques based on inertial data and magnetic field maps. More specifically, your tasks are:

  • Two specific indoor and underground areas are to be scanned with a magnetic field scanner and/or an existing SLAM approach.
  • Several measurements shall be carried out in the scanned areas by a pedestrian wearing an inertial sensor and walking in the area more or less randomly.
  • The magnetic field map shall be integrated as a prior map for the SLAM approach and the measurement results of the SLAM approach shall be analyzed.
  • An alternative new method for pedestrian tracking based on magnetic field maps shall be developed, implemented and investigated.
  • Both methods shall be deeply tested and compared. The effect of using the magnetic field for pedestrian navigation shall be investigated in various experiments.

Your qualifications:

  • Excellent knowledge of positioning algorithms (Kalman filter, particle filter)
  • Excellent JAVA knowledge
  • Good mathematical/signal-processing background
  • Independent working

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

Dr Ing Susanna Kaiser
Institute of Communications and Navigation

Phone: +49 8153 28-2862

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Vacancy 56109

HR department Oberpfaffenhofen

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DLR site Oberpfaffenhofen

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DLR Institute of Communications and Navigation

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