Support subspaces method for synthetic aperture radar automatic target recognition. (30th September 2016)
- Record Type:
- Journal Article
- Title:
- Support subspaces method for synthetic aperture radar automatic target recognition. (30th September 2016)
- Main Title:
- Support subspaces method for synthetic aperture radar automatic target recognition
- Authors:
- Fursov, Vladimir
Zherdev, Denis
Kazanskiy, Nikolay - Abstract:
- This article offers a new object recognition approach that gives high quality using synthetic aperture radar images. The approach includes image preprocessing, clustering and recognition stages. At the image preprocessing stage, we compute the mass centre of object images for better image matching. A conjugation index of a recognition vector is used as a distance function at clustering and recognition stages. We suggest a construction of the so-called support subspaces, which provide high recognition quality with a significant dimension reduction. The results of the experiments demonstrate that the proposed method provides higher recognition quality (97.8%) than such methods as support vector machine (95.9%), deep learning based on multilayer auto-encoder (96.6%) and adaptive boosting (96.1%). The proposed method is stable for objects processed from different angles.
- Is Part Of:
- International journal of advanced robotic systems. Volume 13:Number 5(2016)
- Journal:
- International journal of advanced robotic systems
- Issue:
- Volume 13:Number 5(2016)
- Issue Display:
- Volume 13, Issue 5 (2016)
- Year:
- 2016
- Volume:
- 13
- Issue:
- 5
- Issue Sort Value:
- 2016-0013-0005-0000
- Page Start:
- Page End:
- Publication Date:
- 2016-09-30
- Subjects:
- Conjugation index -- digital image processing -- recognition -- SAR image -- SVM
Robotics -- Periodicals
Robotics
Periodicals
629.892 - Journal URLs:
- http://arx.sagepub.com/ ↗
http://search.epnet.com/direct.asp?db=bch&jid=13CR&scope=site ↗
http://www.intechweb.org/journal.php?id=3 ↗
http://www.uk.sagepub.com/home.nav ↗ - DOI:
- 10.1177/1729881416664848 ↗
- Languages:
- English
- ISSNs:
- 1729-8806
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 6985.xml