Master Thesis, 30HP: Finding the UAV in a Haystack of Birds -- Deep Models for Target Classification in Radar Tracking

Are you a student eager to apply your theoretical knowledge and fresh perspectives to real-world challenges? At Saab, we believe that innovation thrives on new ideas, and your master thesis project could be the spark that ignites our next technological breakthrough.

Your role

We recognize the immense value that students bring to our company. Your academic rigor, combined with your enthusiasm for cutting-edge technology, allows you to approach problems with a unique and insightful lens. At Saab, you'll have the opportunity to collaborate with experienced engineers and specialists, gaining invaluable practical experience while making a tangible contribution to our growth and development.

Background

Achieving an air-situational picture of high quality – a task in which radars play a central role – is essential to ensuring the integrity of the air-space, and in turn, the safety of people and society. A surveillance radar works by emitting energy that is reflected by targets of interest as well as other objects in a surveillance volume, giving rise to unlabeled sets of detections of unknown origin. Through repeated measurement of the surveillance volume and the use of target-tracking algorithms, with a foundation in Bayesian estimation, a situational picture emerges described by an a posteriori probability distribution of targets in the air-space.

In particular, developments in recent years have made it increasingly important to detect and track potentially hostile unmanned aerial vehicles (UAVs), informally known as drones. These objects commonly fly at similar altitudes and velocities to the thousands of birds that may be present in the sky at any given moment. This creates a needle-in-a-haystack problem, where accurate automatic classification of target type is important to avoid overloading the radar operator with bird tracks of little relevance.

Description of the Thesis

The project aims to explore Bayesian methods for target classification, focusing on exploiting behavioral differences between birds and UAVs to determine target class. We are in particular interested in the prospects of likelihood-based classification using learned system models. Depending on the class of system models under consideration, this may also involve learning filters to facilitate likelihood evaluation within a modest computational budget.

A ladder of different system models may be considered, ranging from traditional kinematic models parametrized by a few parameters, models in deep latent spaces, and hybrid models combining both prior knowledge about dynamics of the kinematic state and deep states which may encode additional behavioral information. By investigating system identification along this ladder, the intention of the project is to address how to combine prior structure and model expressiveness to maximize object classification capabilities.

Your profile

The project is suitable for one or two students. You are in the end of your technical master's education in Engineering Physics, Engineering Mathematics, Electrical engineering, Automation and Mechatronics or similar, with an interest for advanced mathematics and numerical methods. Advanced courses in mathematics, in particular Bayesian statistics, is meriting, as well as practical experience of deep learning.

We provide the support and guidance you need to translate your theoretical knowledge into practical solutions. Join us and become a driving force behind Saab's technological advancements!

This position requires that you pass a security vetting based on the current regulations around/of security protection. For positions requiring security clearance additional obligations on citizenship may apply.

Kindly observe that this is an ongoing recruitment process and that the position might be filled before the closing date of the advertisement.

What you will be a part of

Explore a wealth of possibilities. Take on challenges, create smart inventions, and grow beyond. This is a place for curious minds, brave pioneers, and everyone in between. Together, we achieve the extraordinary, each bringing our unique perspectives. Your part matters.

Saab is a leading defense and security company with an enduring purpose, to help nations keep their people and society safe. Empowered by its 28,000 talented people, Saab constantly pushes the boundaries of technology to create a safer and more sustainable world.

Saab designs, manufactures and maintains advanced systems in aeronautics, weapons, command and control, sensors and underwater systems. Saab is headquartered in Sweden. It has major operations all over the world and is part of the domestic defense capability of several nations. Read more about us here.