DocumentCode
144384
Title
Sea clutter statistical characterization using TerraSAR-X data
Author
Makhoul, Eduardo ; Yu Zhan ; Broquetas, Antoni ; Ruiz-Rodon, Josep ; Baumgartner, Stefan
Author_Institution
Signal Theor. & Commun. Dept., Univ. Politec. de Catalunya (UPC), Barcelona, Spain
fYear
2014
fDate
13-18 July 2014
Firstpage
5130
Lastpage
5133
Abstract
The paper presents a preliminary statistical evaluation of the sea clutter returns imaged by a spaceborne synthetic aperture radar (SAR) mission as TerraSAR-X. Two polarimetric data takes, Dual-polarized (Dual-Pol) and Quad-polarized (Quad-Pol), covering the range of incidence angles from 30 to 32 degrees, are considered for the stochastic characterization. The results show that the K-distribution, extendedly assumed statistics for high resolution radar sea clutter imaging, fits well the data´s amplitude. This information jointly with the inverted sea spectrum are used to simulate SAR images of realistic scenarios that can be exploited for proper performance evaluation of ground moving target indication (GMTI) techniques and missions for maritime surveillance.
Keywords
object detection; spaceborne radar; statistical analysis; synthetic aperture radar; GMTI mission; GMTI technique; K-distribution; SAR image simulation; TerraSAR-X data; data amplitude; dual-polarized data; extendedly assumed statistics; ground moving target indication mission; ground moving target indication technique; high resolution radar sea clutter imaging; incidence angle range; inverted sea spectrum; maritime surveillance; polarimetric data; preliminary statistical evaluation; quad-polarized data; realistic scenario; sea clutter return; sea clutter statistical characterization; spaceborne SAR mission; spaceborne synthetic aperture radar mission; stochastic characterization; Clutter; Radar clutter; Radar imaging; Shape; Spaceborne radar; Synthetic aperture radar; sea clutter; simulation; spaceborne synthetic aperture radar (SAR); statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location
Quebec City, QC
Type
conf
DOI
10.1109/IGARSS.2014.6947652
Filename
6947652
Link To Document