We offer a position as an

Early Stage Researcher (M/F/D)

in the Marie Skłodowska-Curie Innovative Training Network Project MENELAOSNT in the field


Coded waveforms for colocated MIMO radar using sparse modelling (ESR9)


A Multiple Input Multiple Output MIMO radar makes use of orthogonal transmit waveforms either in time, in frequency or in code, in order to exploit diversity gain (due to the larger number of degrees of freedom than their phase-array counterparts) and obtain more information from a radar scenario or target. Time Domain Multiplexing at transmit is an easy and cost-effective approach to achieve orthogonality but it implies increasing measurement time with the number of transmitter and a potential ambiguity for Doppler-shift estimation.

An alternative for exploiting MIMO diversity gain in the form of enhanced target detection and localization accuracy is to transmit simultaneously waveforms which are orthogonal in code. These waveforms need to be separated at every receiver in order to create virtual channels for each Tx-Rx module pair. However, such orthogonal signals are separable only when they are perfectly aligned. Therefore, total decoupling is not possible when time delays are considered. To achieve a suboptimal solution signals with good-correlation properties can be investigated, i.e., they should maintain orthogonality over a range of time delays big enough for the particular application, which is in general quite challenging.

The successful candidate will be employed for a maximum period of three years full-time equivalent and receives a generous financial package plus an additional mobility and family allowance according to the rules for Early Stage Researchers (ESRs) in an EU Marie Sklodowska-Curie Actions Innovative Training Networks (ITN). A career development plan will be prepared for each fellow in accordance with his/her supervisor and will include training, planned secondments and outreach activities in partner institutions of the network. The ESR fellows are supposed to complete their PhD thesis by the end of the 3rd year of their employment. For more information please visit the Marie Sklodowska-Curie Actions Innovative Training Networks website.

The main goal of this research project is to find optimum phase-coded waveforms for Compressive Sensing MIMO radar and employ sparse reconstruction to estimate unknown target parameters (delay, Doppler, angle). Additionally, other MIMO waveforms will be considered, time domain multiplexing (TDM), frequency domain multiplexing (FDM) and Doppler domain Multiplexing (DDM) for comparison and validation purposes.


  • Selection of one or more convenient phase-coded waveforms (e.g. zero correlation zone sequences).
  • Assess performance by an ambiguity function based analysis. For comparison purposes frequency hopping codes can be evaluated.
  • Design of optimal codes using innovative techniques such as game theory or genetic algorithms.
  • Signal processing of coded MIMO radar data via sparse modeling.
  • Design of transmit-receive array configuration in combination with the waveform design, eventually considering also adaptive waveform design approaches.
  • Identification of advantages and limitations by synthetic and experimental tests.


  • MSc degree or equivalent in Applied Mathematics, Electrical/Electronic Engineering, Physics, or Computer Science.
  • ESRs must demonstrate that their ability to understand and express themselves in both written and spoken English is sufficiently high for them to derive the full benefit from the network training. Non-native English speakers are required to provide evidence of English language competency. (TOEFL … )
  • Fluent in Matlab (preferred), or, alternatively, Python or C.
  • Some knowledge and experience in a number of the following topics:
    • MIMO radar
    • Signal processing techniques for radar
    • Compressive Sensing and sparse reconstruction methods
    • Waveform design and optimization algorithms
    • Bayesian filtering and adaptive systems


  • USI (ZESS), Siegen, Germany, Prof. Dr. O. Loffeld, Prof. Dr. P. Haring Bolivar, 5 months, for the investigation on design of optimum codes, this secondment is intended to exchange knowledge on construction of codes for different sensors and applications
  • SU (SPIS), Sabanci, Turkey, Prof. Dr. M. Cetin, 2 months, signal processing of coded MIMO data using CS
  • WIS (SAMPL), Israel, Prof. Dr. Y. Eldar, 2 months, performance assessment and signal processing of coded MIMO data using CS


Modern radar systems represent complex sensors with a variety of software-defined degrees of freedom. These systems, however, are not yet capable of self-optimization on the basis of findings derived from measurements.

In the Cognitive Radar department at the Fraunhofer FHR we combine methods of computer science, such as machine learning techniques and artificial intelligence methods, with advanced signal processing and electrical engineering approaches. The aim is to create”smart” sensor systems that are capable of adapting the waveform and the operating parameters to the scene and the mission context in a dynamic manner.

The successful candidate will join a strong and motivated research team with broad experience in MIMO radar, particularly in array design, high-resolution angular estimation, Compressed-Sensing and sparse reconstruction techniques, modulation schemes, Bayesian filtering, and adaptive systems.

More information can be found in the following links:


https://www.fhr.fraunhofer.de/en/businessunits/traffic/Cognitive-automotive-radar.htmlIn the next video we show the potential of sparse reconstruction method OMP for high-resolution angular estimation of targets in real-time using a 4Tx/8Rx MIMO radar:

Recent publications by our group

  1. Giovanneschi, F., Mishra, V., Gonzalez-Huici, M.A., Eldar, Y.C., and Ender, J.H.G, “Dictionary Learning for Adaptive GPR Target Classification”, IEEE Trans. Geoscience and Remote Sensing, 2019.
  2. Gonzalez-Huici, M.A., Mateos-Nunez, D, Simoni, R., Bin Khalid, Farhan, and Eschbaumer, M., “Design of a Sparse MIMO Automotive Radar Front-end”, Eurad 2019.
  3. Mateos-Nunez, A., Simoni, R., Gonzalez-Huici, M.A., and Correas-Serrano, A., “Design of incoherent radar arrays for DoA estimation via group-sparse reconstruction, RadarConf 2019.
  4. [4] Correas-Serrano, A. and Gonzalez-Huici, M.A., “Sparse Reconstruction of Chirplets for Automotive FMCW Radar Interference Mitigation”, ICMIM 2019.
  5. Greiff, C., Mateos-Nunez, D., González-Huici, M.A., and Brüggenwirth, S., „Adaptive transmission for Radar Arrays using Weiss-Weinstein-bounds“, IET Research Journals, Special Issue on Cognitive Radar, Dec. 2018.
  6. Correas-Serrano, A. and González-Huici, M.A., “Experimental Evaluation of Compressive Sensing for DoA Estimation in Automotive Radar”
  7. Mateos-Nunez, A., Gonzalez-Huici,M.A., Simoni, R., and Brüggenwirth, S., “Adaptive channel selection for DoA estimation in MIMO radar”, IEEE International Workshop on Computational Advanced in Multi-Sensor Adaptive Processing CAMSAP, 2017.

Fraunhofer FHR is one of the leading and largest research institutes in Europe in the area of high frequency and radar techniques. For its partners, the institute develops customized concepts, techniques and systems for electromagnetic sensors from the microwave range through to the lower terahertz range. At Fraunhofer FHR, research activities focus on high frequency sensors for high-precision range or position determination as well as imaging systems with resolutions of up to 3.75 mm. The application spectrum of these devices ranges from reconnaissance, surveillance and protection systems to real-time capable sensors for traffic and navigation as well as quality assurance and non-destructive testing. The systems from Fraunhofer FHR are renowned for their reliability and robustness: radar and millimeter wave sensors are ideal for complex tasks, also under critical ambient conditions. They operate under high temperatures, in the presence of vibrations or in zero visibility conditions caused by dense smoke, steam or fog. The techniques and systems developed at Fraunhofer FHR are used, on the one hand, to conduct research on new technologies and designs. On the other hand, the institute – in cooperation with companies, authorities and other public bodies – develops prototypes that are designed to master currently unsolved challenges. The technologies used range from traditional waveguide techniques to highly-integrated silicon-germanium chips with frequencies of up to 300 GHz. The ability to carry out non-contact measurements and penetrate materials opens up numerous possibilities for the localization of objects and persons. Due to their special capabilities resulting from the progress in miniaturization and digitalization, the high frequency sensors from Fraunhofer FHR are an affordable and attractive option for a growing number of application areas.

The position will be located at

Fraunhofer-Institut für Hochfrequenzphysik und Radartechnik FHR
Fraunhofer-Straße 20
55334 Wachtberg, Germany

Supervisor: Prof. Dr. Dirk Heberling, Prof. Dr. Peter Knott

Planned Recruitment date: 1st September 2020.
Eligibility Criteria and Mobility Rule

ESRs must, at the date of recruitment, be in the first four years (full-time equivalent research experience) of their research careers and have not been awarded a doctoral degree. Full-Time Equivalent Research Experience is measured from the date when the researcher obtained the first degree entitling him/her to embark on a doctorate (either in the country in which the degree was obtained or in the country in which the researcher is recruited), even if a doctorate was never started or envisaged. Researchers can be of any nationality.

ESRs must not have resided or carried out their main activity (work, studies, etc.) in the country of the recruiting beneficiary for more than 12 months in the 3 years immediately before the planned recruitment date. Compulsory national service, short stays such as holidays, and time spent as part of a procedure for obtaining refugee status under the Geneva Convention are not taken into account.