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/Job opportunities/Innovative Sparse Antenna Array and Signal Processing for MIMO Radar Angle Estimation

Innovative Sparse Antenna Array and Signal Processing for MIMO Radar Angle Estimation

Internship/thesis - Leuven | More than two weeks ago

Define the next generation MIMO radar with your innovative antenna array design

​The multiple-input-multiple-output (MIMO) concept is widely used in radar applications. It achieves a high angular resolution with a limited number of physical antennas by creating a large virtual aperture. In conventional MIMO radars, the virtual array elements are equidistantly spaced with half wavelength separation, ensuring that the direction of arrival (DoA) estimation is unambiguous and avoiding grating lobes. 

With the increasing demand for the high-resolution radars, especially in the angular domain, sparse antenna array with advanced signal processing is a hot topic in both academia and industry. It allows improving the angular resolution without increasing the antenna count. However, sparse antenna arrays with average inter-element spacing larger than half wavelength create grating lobes and sidelobes in the angular spectrum. 

In this MS project, the student will investigate state-of-the-art sparse antenna array structures in the literature for high-resolution DoA estimation. Further, he/she will design innovative antenna array structure and develop the associated signal processing, optimizing resolution, sidelobes and grating lobes. Matlab modeling will be used to for the analysis. Minimizing the computational complexity will be part of the study. Finally, the proposed approach will be evaluated using real measurement data of a MIMO radar.

The work will include:

  • Literature survey of state-of-the-art sparse antenna array and corresponding angle estimation algorithms.
  • Design and analysis of different sparse array structures and algorithmic solutions.
  • Modeling: performance evaluation of investigated sparse array structures and algorithms.
  • Computational complexity analysis.
  • Validation of the proposed approach using real radar data.

The successful candidate must show a strong understanding of array signal processing and linear algebra. Proficiency with Matlab is a must. Some knowledge of compressive sensing and optimization is a plus.

Type of project and duration:

  • Master Thesis internship (6 months)
  • Preceded by optional summer internship (max 3 months)

Required degree: Master of Engineering Technology, Master of Engineering Science

Required background: Electrotechnics/Electrical Engineering

Responsible scientist(s): For further information or for application, please contact: Yuliang Sun (

Only for self-supporting students.