Annual Report 2022

Promotionen am Fraunhofer FHR 2022

Fraunhofer FHR offers scientists optimal conditions to write their PhD thesis at the institute. In doing so, the institute supports the employees in each case precisely tailored to their individual interests and paths to the doctorate. Four employees who completed their doctorates in 2022 report on their experiences.

Dr. Nadav Neuberger

Dr. Nadav Neuberger from the Signal Processing for Surveillance Radar group in the Array based Radar Imaging Department successfully defended his dissertation entitled »Signal Processing for Space Surveillance Radar« in February 2022. Dr. Neuberger earned his bachelor‘s and master‘s degrees in electrical engineering in Israel and has worked as an electrical engineer in the private sector in large companies and small startups. In 2018, an exciting research position brought him to the Institute and he started his PhD in Electrical Engineering and Computer Science at the University of Siegen under Prof. Dr.-Ing. Joachim Ender.


With his doctoral thesis, he followed his interest in going deeper into the theory of radar signal processing. »Radar signal processing in itself has been around for decades. However, there is a great potential for new methods that are better suited for the space surveillance scenario – especially for the detection of space debris in low-Earth orbit. In my work, I focused on new signal processing methods tailored to debris detection and parameter estimation,« Dr. Neuberger says. The topic arose from his task of developing signal processing for GESTRA. Some of the new methods include a new Rx beamformer for accurate direction-of-arrival (DOA) estimation and sensitive detection. Similarly, two new FM-encoded waveforms will be introduced to solve various sidelobe challenges within range Doppler processing.


»The institute and my colleagues have supported my PhD perfectly in every way. Likewise, I am very grateful for the excellent supervision by Prof. Ender – as a leader of the worldwide radar community, he makes an invaluable contribution to students and scientific colleagues,« Dr. Neuberger summarizes.

Dr. Stephan Palm

At the end of December 2021, Dr. Stephan Palm, a member of the SAR and Algorithms @mmW group in the High Frequency Radar and Applications department, successfully defended his PhD thesis »Mapping of urban scenes by single-channel mmW FMCW SAR on circular flight and curved car trajectories« at the TU Munich. His doctoral supervisor was Prof. Dr.-Ing. Uwe Stilla.


The thesis deals with the development of an airborne circular SAR system including new data processing methods, combined with high-resolution imaging of roads and facades (radar mobile mapping) and 3D point cloud extraction. Dr. Palm published the results in three journal papers and at various conferences. »I was able to show what is possible with a single-channel SAR system using circular geometry in the W-band: azimuth resolution down to 1 cm, height resolution down to 10 cm, and detection and visualization of moving targets such as people and vehicles. The biggest challenge was to develop a system capable of acquiring experimental 360° data in the W-band in the first place. For this purpose, among other things, companies had to be found that manufacture subcomponents of the special hardware. Likewise, processing the amount of data from the 3D point cloud was very challenging, i.e., setting up the processing chain and making it efficient,« says Dr. Palm.  


Dr. Palm came to Fraunhofer FHR in 2011 after completing his studies in technical computer science at RWTH, and started his doctoral studies in 2013. »I can only report good things about my doctoral conditions at the institute: I had a high degree of creative freedom for my work, as its content fit very well with our projects. Department heads and colleagues always supported me and were always on hand with advice and support. The opportunity to attend conferences and exchange ideas with other universities was also ideal. For example, at the beginning of my doctorate, I had a 10-day stay at the University of Zurich as a start to SAR processing,« says Dr. Palm looking back.

Dr. Simon Wagner

Dr. Simon Wagner, Group Leader Machine Learning for Radar Applications in the Department of Cognitive Radar (KR), successfully defended his doctoral thesis on »Radar Target Classification via Sparse Decomposition« at the Chair of Highest Frequency Technology and Quantum Electronics at the University of Siegen under Prof. Dr.-Ing. Peter Haring Bolívar in April 2022. Doctoral advisor and supervisor at Fraunhofer FHR was Prof. Dr.-Ing. Joachim Ender.  


In 2012, Dr. Wagner visited Fraunhofer FHR as a student of electrical engineering in Trier and got to know Prof. Ender, who developed the rough direction of the research approaches together with him. Thus, Dr. Wagner wrote his master‘s thesis at the institute and has been working as a scientist in the KR department (until 2014 PSK) ever since. The further development of the master‘s topic resulted in the topic of the doctoral thesis. In it, he investigated how to detect different types of reflectors in ISAR images. In one application, a TIRA-measured aircraft was divided into the reflectors engines and point targets, where the tail created behind engines was exploited. Dr. Wagner found a physical model and applied it for the first time in a classification method that describes this phenomenon. The determination of the position and number of thrusters provides the classifier with valuable additional information for the classification of the object.  


He wrote his doctoral thesis detached from his daily work and so there were always project-related breaks in the doctoral work. »On the one hand, it is a challenge to persevere over a longer period of time, but on the other hand, I had new ideas again after the breaks,« says Dr. Wagner. The institute has always supported him well in his endeavor. »The mathematician colleagues in my department helped me a lot with the proofs in my thesis. Visits to the radar conferences in London, Pisa and New York were also great – at EURAD 2016, I won the Best Paper Award with my topic,« Dr. Wagner sums up.

Dr. Reinhard Panhuber

In November 2022, Dr. Reinhard Panhuber successfully defended his dissertation »Partitioning of Radar Signals in Stationary and Ground Moving Targets by use of Low-Rank and Compressed Sensing Methods« at the University of Siegen. His thesis advisor was Prof. Dr.-Ing. Joachim Ender, supervisor at the institute was his group leader Dr. Ludger Prünte.


Dr. Panhuber studied information electronics at Johannes Kepler University Linz/Austria and joined Fraunhofer FHR in 2015 – in the MIMO radars and multistatics group of the Array based Radar Imaging department. In 2018, he started his PhD in the context of an industrial project. He dealt with the treatment of ground clutter in the detection of moving targets, such as cars or ships, from aircraft (Airborne – Ground Moving Target Indication/GMTI). Classically, an algorithm called Space Time Adaptive Processing (STAP) is used for GMTI. This enables the suppression of ground clutter, i.e. echoes from the earth‘s surface that are superimposed on the reflections of moving targets. In STAP, an adaptive filter is trained using real measurement data. STAP requires certain preconditions such as homogeneously distributed landscapes. His idea was to use modern mathematical methods like Compressed Sensing (CS), Affine Rank Minimization (ARM) and their combination Robust Principle Component Analysis (RPCA) to solve the problem of residual ground clutter. From this scenario, he developed a two-stage solution: the Auto-Clutter Focus (ACF) algorithm, a robust, patent-pending estimation technique that can estimate aircraft speed and pitch and yaw angles using the clutter signals, and the Projection Matched Filter (PMF), a powerful filter that uses the parameters estimated using the ACF algorithm.  


»The PhD conditions were very good for me. I could fully concentrate on the topic. During the familiarization with the topic, Dr. Prünte in particular supported me very much and I learned extremely many new things. As the work progressed, I was naturally more on my own. You need a lot of initiative and commitment,« he concludes.