Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Knowledge Exploitation for Human Micro-Doppler Classification
Department of Electrical and Electronics Engineering, TOBB University of Economics and Technology, Ankara 06560, Turkey; and Meteksan Defense Industries, Inc., Ankara 06560, Turkey.
e Department of Electrical and Electronics Engineering, TOBB University of Economics and Technology, Ankara 06560, Turkey; and the TUBITAK Space Technologies Research Institute, Ankara 06800, Turkey.
Department of Electrical and Electronics Engineering, TOBB University of Economics and Technology, Ankara 06560..
Department of Electrical and Electronics Engineering, Turgut Ozal University, Ankara 06560, Turkey..
Show others and affiliations
2015 (English)In: IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, E-ISSN 1558-0571, Vol. 12, no 10, 2125-2129 p.Article in journal (Refereed) Published
Abstract [en]

Micro-Doppler radar signatures have great potential for classifying pedestrians and animals, as well as their motion pattern, in a variety of surveillance applications. Due to the many degrees of freedom involved, real data need to be complemented with accurate simulated radar data to be able to successfully design and test radar signal processing algorithms. In many cases, the ability to collect real data is limited by monetary and practical considerations, whereas in a simulated environment, any desired scenario may be generated. Motion capture (MOCAP) has been used in several works to simulate the human micro-Doppler signature measured by radar; however, validation of the approach has only been done based on visual comparisons of micro-Doppler signatures. This work validates and, more importantly, extends the exploitation of MOCAP data not just to simulate micro-Doppler signatures but also to use the simulated signatures as a source of a priori knowledge to improve the classification performance of real radar data, particularly in the case when the total amount of data is small.

Place, publisher, year, edition, pages
IEEE Press, 2015. Vol. 12, no 10, 2125-2129 p.
Keyword [en]
Classification; human micro-Doppler; knowledge-based signal processing; motion capture (MOCAP)
National Category
Control Engineering Signal Processing
Identifiers
URN: urn:nbn:se:liu:diva-120433DOI: 10.1109/LGRS.2015.2452311ISI: 000359576400024OAI: oai:DiVA.org:liu-120433DiVA: diva2:845129
Funder
Security Link
Note

Funders: SAAB; EU FP7 Project [PIRG-GA-2010-268276]; TUBITAK Career [113E105]

Available from: 2015-08-10 Created: 2015-08-10 Last updated: 2017-12-04

Open Access in DiVA

fulltext(1926 kB)785 downloads
File information
File name FULLTEXT01.pdfFile size 1926 kBChecksum SHA-512
499e0a49d7ce06c56d65d8f1a6c08d607d42c206e599004025ec0b391fe77530fcf6dd424e8a85c88336b6dcc6318da7cbbf6e0d0621487c9cd28d57ed01cef7
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Authority records BETA

Hendeby, GustafGustafsson, Fredrik

Search in DiVA

By author/editor
Hendeby, GustafGustafsson, Fredrik
By organisation
Automatic ControlFaculty of Science & Engineering
In the same journal
IEEE Geoscience and Remote Sensing Letters
Control EngineeringSignal Processing

Search outside of DiVA

GoogleGoogle Scholar
Total: 785 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 599 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf