Saab Deutschland GmbH Bremen, in collaboration with the Department of Communication Engineering at the University of Bremen (ANT), is offering a Master’s Thesis opportunity titled:

Multi-Resolution Spectral Detection Algorithms for Signal Intelligence

Master Thesis Overview:

In the domain of signal intelligence (SIGINT), a critical challenge lies in the detection and localization of diverse radio frequency (RF) transmissions—ranging from short-duration pulsed signals to narrowband continuous-wave emissions—without prior knowledge of signal characteristics.

Operational demands require a single receiver system to effectively identify such signals across a shared spectral environment, under stringent constraints.

Traditional frequency-domain detection methods are limited by a fixed time-bandwidth product, which compromises performance when dealing with signals of varying durations and bandwidths.

To address this, multi-resolution signal analysis techniques have emerged as essential tools, enabling adaptive resolution tailored to signal properties.

Furthermore, advancements in RF technology necessitate monitoring of higher frequency bands and wider instantaneous bandwidths, all while deploying algorithms on mobile platforms with strict size, weight, and power (SWaP) limitations.

Consequently, computational efficiency and real-time feasibility are paramount design considerations.

Thesis Objectives:

This research will focus on the development, analysis, and implementation of multi-resolution spectral detection algorithms tailored for non-cooperative signal intelligence scenarios.

The work will include:

• Literature Review: Comprehensive analysis of state-of-the-art multi-resolution detection techniques, with emphasis on their applicability in non-cooperative and dynamic RF environments.

• Theoretical Evaluation: Comparative assessment of selected methods in terms of computational complexity, detection probability, and false alarm rate under varying signal conditions.

• Implementation and Validation: Development and testing of at least one multi-resolution detection algorithm using MATLAB or Python. Performance will be evaluated using both synthetic signal simulations and real-world RF recordings.

Candidate Requirements:

Applicants must meet the following criteria:

• Currently enrolled in a Master’s program in University of Bremen in the following fields of:

• Communication and Information Technology (CIT)

• Electrical Engineering and Information Technology

• Space Sciences and Technologies (Space-ST)

• Strong academic background in Digital Signal Processing and Wireless Communications, with documented grades of 2.0 or better in relevant courses.

• Demonstrated motivation, independence, and high-quality academic performance.

• Proficiency in MATLAB or scientific Python programming.

• Prior practical experience through internships, research assistantships, or project work in signal processing or communications is highly desirable.

• Familiarity with version control systems such as Git is considered an advantage.

What Saab Deutschland GmbH Bremen Offers:

• Flexible working hours (flexitime) and the option for remote or hybrid work

• Supportive work environment with emphasis on work-life balance

• Wellness initiatives including free access to water and fresh fruit

• Regular employee engagement events, including summer and winter parties, as well as team-building activities

How to Apply:

Interested candidates are invited to submit their application via email to applications@ant.uni-bremen.de to Prof. Dr.-Ing. Dekorsy with the subject line: "Reference: Master Thesis – [Your Full Name]"

Please include the following documents in your application:

- Curriculum Vitae (CV)

- Official transcript of records (with grades)

- A brief motivation letter outlining your interest in the topic and relevant experience

Applications will be reviewed on a rolling basis. Early submission is encouraged.