Institute of Electrical and Electronic Engineers (IEEE)
IEEE Geoscience and Remote Sensing Letters
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.
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.
ADA Accessible Version
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.