Enhancing Angular Resolution Using Neural Networks in Automotive Radars

Ignacio Roldan *, Francesco Fioranelli, Alexander Yarovoy

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review


Poor angular resolution is one of the main disadvantages of automotive radars, and the reason why lidar technology is widely used in the automotive industry. For a fixed frequency, the angular resolution of a conventional Multiple-Input Multiple-Output (MIMO) radar is limited by the number of physical antennas, and therefore improve the resolution involves increasing the size and the cost of the system, critical constraints in the automotive industry. In this work, a novel approach is presented to overcome this limitation, where a Neural Network (NN) is used to enhance the angle resolution of a MIMO radar without increasing the number of physical elements, but extrapolating the antennas signals in a teacher-student fashion. The method was validated using real data of stationary pedestrians captured outdoors, demonstrating an effective increase of three times the antenna array size. To the best knowledge of the authors, this is the first method that includes an evaluation metric in the final stages of the processing pipeline, enforcing the conservation of the target's angular shape, key for subsequent object classification.

Original languageEnglish
Title of host publicationProceedings of the 18th European Radar Conference
Number of pages4
ISBN (Electronic)978-2-87487-065-1
ISBN (Print)978-1-6654-4723-2
Publication statusPublished - 2022
EventThe 18th European Radar Conference - London, United Kingdom
Duration: 5 Apr 20227 Apr 2022


ConferenceThe 18th European Radar Conference
Country/TerritoryUnited Kingdom

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care

Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


  • automotive radar
  • MIMO
  • angular resolution
  • neural networks


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