Title :
Backscattering Feature Analysis and Recognition of Civilian Aircraft in TerraSAR-X Images
Author :
Jiehong Chen ; Bo Zhang ; Chao Wang
Author_Institution :
Key Lab. of Digital Earth Sci., Inst. of Remote Sensing & Digital Earth, Beijing, China
Abstract :
This letter first analyzes the scattering features of civilian aircraft (CA) using high-resolution TerraSAR-X images of the Hong Kong International Airport based on the electromagnetic scattering theory. The main stable scattering features are found to be salient points. Then, a salient point vector (SPV) is proposed to describe the salient points. By adding two relaxation variables to the matching process, the SPV becomes both translationally and rotationally invariant over a certain orientation range. In addition, a recognition scheme is designed to validate the scattering analysis and the SPV descriptor. Finally, 43 test chips are collected from another TerraSAR-X image acquired in November 2013 in the same location with similar imaging parameters. The test chips are applied to validate the analysis, the SPV descriptor, and the recognition scheme. The results of the experiment indicate that the recognition rate of the Boeing 747 CA reaches 80% and that the scattering features of the aircraft are rotationally invariant to within at least 5°. This research verifies the potential application of CA monitoring using high-resolution synthetic aperture radar images.
Keywords :
aircraft; image recognition; image resolution; remote sensing by radar; synthetic aperture radar; Boeing 747 CA; Hong Kong International Airport; backscattering feature analysis; civilian aircraft; electromagnetic scattering theory; high-resolution TerraSAR-X images; high-resolution synthetic aperture radar images; recognition scheme; salient point vector; Backscatter; Detectors; Feature extraction; Image recognition; Remote sensing; Scattering; Synthetic aperture radar; Civilian aircraft (CA); recognition; salient point; synthetic aperture radar (SAR);
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2014.2362845