Master thesis (f/m/x): Multipath mitigation for object tracking with radar data

The DLR Institute of Communications and Navigation is dedicated to mission-oriented research in selected areas of communications and navigation. Its work ranges from the theoretical foundations to the demonstration of new procedures and systems in a real environment and is embedded in DLR's Space, Aeronautics, Transport, Security and Digitalization programs.

What To Expect

The Nautical Systems department of the DLR Institute of Communications and Navigation develops and tests new procedures and technologies for shore-based and on-board support in ship navigation, among other things. The focus of the “Traffic Systems” (VLS) working group is on the fusion and evaluation of data on moving maritime objects from different sensors and sources.

You will research and implement multipath mitigation techniques for multi-object tracking algorithms using maritime radar data. Then, the performance of the developed methods shall be tested against the results from classical tracking methods, findings shall be documented and suggestions made on further improvement/applicability of the tested approaches.

Your tasks

• provide an overview of the state-of-the-art point object and extended object MOT algorithms with multi-path mitigation
• implement several selected MOT algorithms and analyze their performance on a set of representative maritime radar data with multipath effects
• work on the parameterization and algorithmic improvements of the selected tracking algorithm and address the accuracy and computational issues
• compare the performance of the proposed algorithms to the one of the standard tracking algorithms without multi-path mitigation
• document and present the results, provide suggestions for further improvements.

Your profile

• completed bachelor's degree in physics, mathematics, electrical engineering, communications engineering or other courses relevant to the position
• basic knowledge of statistical signal processing including Bayesian estimation methods (Kalman filtering, Particle filtering) and knowledge with classical tracking algorithms
• Programming skills in Linux with Python and knowledge of C++ and a solid mathematical foundation are required.
• interest in estimation algorithms, statistical signal processing, object tracking, etc.
• able to work well in teams and structured working style
• knowledge of German and good written and spoken English

We look forward to getting to know you!

If you have any questions about this position (Vacancy-ID 2997) please contact:

Dr. Nis Meinert

Tel.: