mlsanityData to 7 Oct 2026

Coherent, super resolved radar beamforming using self-supervised learning

arXiv 2106.13085 ↗First posted 21 Jun 2021eess.SP cs.AI cs.ROcited by 4

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Abstract (arXiv)

High resolution automotive radar sensors are required in order to meet the high bar of autonomous vehicles needs and regulations. However, current radar systems are limited in their angular resolution causing a technological gap. An industry and academic trend to improve angular resolution by increasing the number of physical channels, also increases system complexity, requires sensitive calibration processes, lowers robustness to hardware malfunctions and drives higher costs. We offer an alternative approach, named Radar signal Reconstruction using Self Supervision (R2-S2), which significantly improves the angular resolution of a given radar array without increasing the number of physical channels. R2-S2 is a family of algorithms which use a Deep Neural Network (DNN) with complex range-Doppler radar data as input and trained in a self-supervised method using a loss function which operates in multiple data representation spaces. Improvement of 4x in angular resolution was demonstrated using a real-world dataset collected in urban and highway environments during clear and rainy weather conditions.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 26 of its 67 references that are in the map. First posted on arXiv 21 Jun 2021.

Builds on

26 of 67 references.

References · 26

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14 more
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Cited by year

Citing papers per year: 2021: 1; 2022: 2; 2023: 1.

4 papers.

  1. 2021Self-Supervised Radio-Visual Representation Learning for 6G Sensingcited by 6
  2. 2022Physics and semantic informed multi-sensor calibration via optimization theory and self-supervised learningcited by 4
  3. 2022Look, Radiate, and Learn: Self-Supervised Localisation via Radio-Visual Correspondencecited by 3
  4. 2023Super-Resolution Radar Imaging with Sparse Arrays Using a Deep Neural Network Trained with Enhanced Virtual Datacited by 0