DocumentCode
1826258
Title
Hierarchical ship classifier for airborne synthetic aperture radar (SAR) images
Author
Valin, Pierre ; Tessier, Yves ; Jouan, Alexandre
Author_Institution
Dept. of Res. & Dev., Lockheed Martin Canada, Montreal, Que., Canada
Volume
2
fYear
1999
fDate
24-27 Oct. 1999
Firstpage
1230
Abstract
Lockheed Martin Canada has developed an agent-based adaptable data fusion testbed (ADFT) within the knowledge based system (KBS) architecture which is currently made of a multi-sensor data fusion (MSDF) module and an image support module (ISM). The MSDF module fuses the information provided by nonimaging (2D-radar, ESM) sensors and the various propositions provided by the ISM when processing a synthetic aperture radar (SAR) image. Currently, the ISM processes, simulated and/or real images of ships through a four-step hierarchical classifier that can extract attributes such as ship length, ship category, ship type and ship class. The SAR classifier can distinguish between merchant and combatant categories and can select amongst 5 combatant types. Tests on simulated and real SAR images show a good recognition rate up to the ship type for merchant and line ships.
Keywords
airborne radar; image classification; knowledge based systems; military radar; radar computing; radar imaging; radar target recognition; sensor fusion; ships; synthetic aperture radar; 2D-radar; ESM; Lockheed Martin Canada; agent-based adaptable data fusion testbed; airborne synthetic aperture radar images; combatant ships; hierarchical ship classifier; image support module; knowledge based system architecture; merchant ships; multi-sensor data fusion module; nonimaging sensors; real SAR images; recognition rate; ship category; ship class; ship length; ship type; simulated SAR images; Data mining; Fuses; Image recognition; Image sensors; Knowledge based systems; Marine vehicles; Sensor fusion; Sensor phenomena and characterization; Synthetic aperture radar; System testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Signals, Systems, and Computers, 1999. Conference Record of the Thirty-Third Asilomar Conference on
Conference_Location
Pacific Grove, CA, USA
ISSN
1058-6393
Print_ISBN
0-7803-5700-0
Type
conf
DOI
10.1109/ACSSC.1999.831903
Filename
831903
Link To Document