Advances in Radio Science
Advances in Radio Science
ARS
Articles | Volume 19
Articles | Volume 19
https://doi.org/10.5194/ars-19-71-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ars-19-71-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19
17 Dec 2021
 | 17 Dec 2021

Dynamic Eigenimage Based Background and Clutter Suppression for Ultra Short-Range Radar

Matthias G. Ehrnsperger, Maximilian Noll, Stefan Punzet, Uwe Siart, and Thomas F. Eibert

Viewed

Total article views: 1,085 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
727 324 34 1,085 41 21
  • HTML: 727
  • PDF: 324
  • XML: 34
  • Total: 1,085
  • BibTeX: 41
  • EndNote: 21
Views and downloads (calculated since 17 Dec 2021)
Cumulative views and downloads (calculated since 17 Dec 2021)

Viewed (geographical distribution)

Total article views: 1,076 (including HTML, PDF, and XML) Thereof 1,076 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 13 Dec 2024
Download
Short summary
In the paper we describe how the detection of living objects, such as people and animals, can be significantly improved. It is particularly important to detect people in dangerous environments to protect them. For such a detection task we use a radar system. Radar, because the detection also has to work at night and if it rains or snows, these are the situations when other systems, i.e. cameras, fail. Our experiments showed that many radar applications can benefit from our approach.
Read more