Radars capable to detect a target position in a 3D space are widely used in a number of application scenarios, such as automotive, industrial, unmanned aerial vehicle etc. One method that allow such a feature is to use a 2D MIMO array capable of detecting the position of a target in terms of range and angular position on the azimuth and elevation angle.
In the Institute of Microwave Engineering of the Ulm University a new method for the performance assessment of a 2D MIMO array and for the optimization of its element positions has been developed. The optimization of the array element positions is performed through a genetic algorithm. The genetic algorithm leads to a solution that maximize the radar angular field-of-view with low probability to get ambiguities in the target detection while reducing the radar angular resolution in both azimuth and elevation angles. The resulting array elements form a 2D MIMO sparse array.
The objective of this thesis is to add additional features to the genetic algorithm, so that it will be possible to obtain as output a 2D MIMO array based on a circular geometry. To this purpose, multiple approaches can be implemented and compared.
The resulting array/s should be produced and calibrated. The array performance should be also evaluated and compared to the one of a generic 2D MIMO sparse array.
In order to achieve the goal explained above, an array of circular polarized antenna should be also designed and characterized. This array would be used as single element of the 2D MIMO array.
In the first part of the work a literature review on the actual status of the research in this field is required.
As for the software that can be used, the genetic algorithm for optimization of the antenna array positions should be implemented using MATLAB. The design of the single element of the array can be performed either using CST Microwave Studio or Ansys HFSS.
As for prerequisites, it is strongly advised to be familiar with the use of a 3D full-wave electromagnetic software (e.g. CST Microwave Studio, Ansys HFSS) and MATLAB. Moreover, a strong understanding of the concepts of the “Propagation and Antenna” and “Radar-und Hochfrequenzsensoren” courses is required.
Tasks may be modified according to the progress of work.