Master thesis (f/m/x) - Development of the Dynamic Grid-based methods

Master thesis (f/m/x) - Development of the Dynamic Grid-based methods

Join to apply for the Master thesis (f/m/x) - Development of the Dynamic Grid-based methods role at German Aerospace Center (DLR)

The DLR Institute of Communications and Navigation is dedicated to mission-oriented research in selected areas of communications and navigation. Its work ranges from theoretical foundations to 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 is to develop a basic version of the non‑parametric Dynamic Grid algorithm for extended object tracking using maritime radar data. Then, the estimation results shall be compared to the ones of the object‑level parametric trackers using real recorded radar data and ideas shall be investigated for the method's accuracy and runtime performance improvement.

Your tasks

• provide an overview of the state‑of‑the‑art related methods with a focus on radar data and maritime applications
• implement a basic version of a grid algorithm for a single‑ and multiple‑radar configurations
• work on the configuration and propose algorithmic improvements of the tracker and address the accuracy and computational issues
• analyze the performance of the developed tracker using a set of representative maritime radar data
• compare the performance of the proposed algorithm to the one of the standard state‑of‑the‑art object‑level tracker
• document and present the results and findings, provide suggestions for further improvements

What You Bring

• completed bachelor's degree in physics, mathematics, electrical engineering, communications engineering or other courses of study relevant to the position
• basic knowledge of statistical signal processing including Bayesian estimation methods (Kalman filtering, Particle filtering)
• Programming experience in Linux with Python, as well as an interest in GPU‑accelerated computing and knowledge of C++
• 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 offer

DLR stands for diversity, appreciation and equality for all people. We promote independent work and the individual development of our employees both personally and professionally. To this end, we offer numerous training and development opportunities. Equal opportunities are of particular importance to us, which is why we want to increase the proportion of women in science and management in particular. Applicants with severe disabilities will be given preference if they are qualified.

We look forward to getting to know you!

For questions about this position (Vacancy-ID 2998) please contact:

Dr. Nis Meinert
Tel.:

Seniority level: Internship
Employment type: Full-time
Job function: Education and Training
Industries: Research Services

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Job location: Neustrelitz, Mecklenburg-West Pomerania, Germany