Document Type
Article
Language
eng
Publication Date
11-2017
Publisher
Institute of Electrical and Electronic Engineers (IEEE)
Source Publication
IEEE Geoscience and Remote Sensing Letters
Source ISSN
1545-598X
Original Item ID
DOI: 10.1109/LGRS.2017.2750662
Abstract
Hankel rank reduction (HRR) is a method that, by prearranging the data in a Hankel matrix and performing rank reduction via singular value decomposition, suppresses the noise of a time-history vector comprised of the superposition of a finite number of sinusoids. In this letter, the HRR method is studied for performing clutter suppression in synthetic aperture radar (SAR)-based vibrometry. Specifically, three different applications of the HRR method are presented. First, resembling the SAR slow-time signal model, the HRR method is utilized for separating a chirp signal immersed in a sinusoidal clutter. Second, using simulated airborne SAR data with 10 dB of signal-to-clutter ratio, the HRR method is applied to perform target isolation and to improve the results of an SAR-based vibration estimation algorithm. Finally, the vibrometry approach combined with the HRR method is validated using actual airborne SAR data.
Recommended Citation
Pérez, Francisco; Santhanam, Balu; Dunkel, Ranlf; and Hayat, Majeed M., "Clutter Suppression via Hankel Rank Reduction for DFrFT-Based Vibrometry Applied to SAR" (2017). Electrical and Computer Engineering Faculty Research and Publications. 544.
https://epublications.marquette.edu/electric_fac/544
ADA Accessible Version
Comments
Accepted version. IEEE Geoscience and Remote Sensing Letters, Vol. 14, No. 11 (November 2017) : 2052-2056. DOI. © 2017 Institute of Electrical and Electronic Engineers (IEEE). Used with permission.
Majeed M. Hayat was affiliated with University of New Mexico, Albuquerque at the time of publication.