Open AccessInteresting components detection for space satellites from inverse synthetic aperture radar image via feature probabilistic estimation
Author(s) -
Xu Zhiwei,
Zhang Lei,
Xing Mengdao,
Deneen Karen M.,
Ran Lei
Publication year - 2015
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2014.0632
Subject(s) - inverse synthetic aperture radar , computer science , synthetic aperture radar , artificial intelligence , probabilistic logic , robustness (evolution) , computer vision , feature vector , radar imaging , pattern recognition (psychology) , radar , remote sensing , geology , telecommunications , biochemistry , chemistry , gene
Since inverse synthetic aperture radar (ISAR) imaging is a valuable technique in the identification of space satellites, it can potentially detect interesting components of space satellites in ISAR images to further conduct identification. This study proposes a novel method, defined as feature probabilistic estimation (FPE), to detect interesting components of space satellites based on ISAR image registration. In FPE, area feature registration is provoked to establish the relationship between space satellites and off‐line templates of interesting components, followed by detection accuracy based on weighted Gaussian probabilistic density function. Electromagnetic simulations with different aspects, interesting components' structures and scenery noise demonstrate the efficiency and robustness of the proposed FPE, compared with the normalised cross coefficient.