Title :
Feature extraction for electrically large ducts using adaptive Gaussian processing
Author :
Trintinalia, L.C. ; Hao Ling
Author_Institution :
Dept. of Electr. & Comput. Eng., Texas Univ., Austin, TX, USA
Abstract :
We present a new inverse SAR image processing algorithm, that allows the analysis of multi-aspect, multi-frequency scattered signals containing not only persistent scattering centers but also other strong aspect-dependent mechanisms, such as ducts. This technique allows the automatic separation of those persistent scattering center features from the more angular dependent mechanisms. It should be particularly useful as a diagnostic tool for analyzing chamber measurement data.
Keywords :
Gaussian processes; adaptive signal processing; electromagnetic wave scattering; feature extraction; image recognition; radar cross-sections; radar imaging; synthetic aperture radar; adaptive Gaussian processing; angular dependent mechanisms; chamber measurement data; diagnostic tool; electrically large ducts; feature extraction; inverse SAR image processing algorithm; multi-aspect multi-frequency scattered signals; persistent scattering centers; strong aspect-dependent mechanisms; Algorithm design and analysis; Data analysis; Ducts; Feature extraction; Image analysis; Image processing; Particle measurements; Scattering; Signal analysis; Signal processing;
Conference_Titel :
Antennas and Propagation Society International Symposium, 1996. AP-S. Digest
Conference_Location :
Baltimore, MD, USA
Print_ISBN :
0-7803-3216-4
DOI :
10.1109/APS.1996.549676
