Geometrical Shapes Detection in High-Resolution THz SAR Image

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

  • Aman Batra - , Universität Duisburg-Essen (Autor:in)
  • Michael Wiemeler - , Universität Duisburg-Essen (Autor:in)
  • Diana Gohringer - , Professur für Adaptive Dynamische Systeme (Autor:in)
  • Thomas Kaiser - , Universität Duisburg-Essen (Autor:in)

Abstract

The novel extension of the synthetic aperture radar (SAR) technique to the emerging THz spectrum enables a new era of short-range applications such as object recognition, which is presently dominated by the use of optical and infrared sensors. Despite the availability of a large sensing range and penetration depth at the microwave spectrum, analysis of the objects based on geometric shapes is limited due to the lower spatial resolution. In this paper, the detection of geometrical shapes in a high-resolution THz SAR image is investigated. Foremost, a high-resolution environment, which consists of circular, rectangular, and triangular objects is mapped at the frequency spectrum of 325-500 GHz. Further, the map is processed to reduce the artifacts. Finally, the shape detection is addressed based on acquiring the geometric properties of the object. The detected objects can be localized with sub-mm accuracy associated with the spatial resolution.

Details

OriginalspracheEnglisch
Titel2022 19th European Radar Conference, EuRAD 2022
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten213-216
Seitenumfang4
ISBN (elektronisch)9782874870712
PublikationsstatusVeröffentlicht - 2022
Peer-Review-StatusJa

Konferenz

Titel19th European Radar Conference, EuRAD 2022
Dauer28 - 30 September 2022
StadtMilan
LandItalien

Externe IDs

ORCID /0000-0003-2571-8441/work/159607520

Schlagworte

Schlagwörter

  • object detection, object recognition, sar imaging, thz imaging