MASTER OF SCIENCE THESIS DEFENSE BY: Prabin K. Shrestha
When: Monday,
August 14, 2017
10:00 AM
-
12:00 PM
Where: Science & Engineering Building, Lester W. Cory Conference Room: Room 213A
Cost: Free
Description: TOPIC: APPLICATION OF MUSIC ALGORITHM FOR SEPARATING GROUND AND VEGETATION COMPONENTS IN POL-INSAR MEASUREMENTS
LOCATION: Lester W. Cory Conference Room, Science & Engineering Building (SENG), Room 213A
ABSTRACT:
Interferometric Synthetic Aperture Radar (InSAR) is used to generate Digital Elevation Map (DEM) from multiple high resolution SAR images. The phase values of the complex reflection images are used to yield scattering phase center (SPC) which is then used to extract elevation information for each pixel of an image. Interferometry assumes that the return from a pixel can be associated with a single SPC at a fixed elevation. This is not the case for forested terrain as elevation of vegetation and elevation of ground results in two SPCs leading to errors in DEM estimates of the terrain. Fully polarimetric SAR (PolSAR) measurements have the potential to separate different scattering mechanisms based on their polarimetric signatures. The multiple signal classification (MUSIC) algorithm is an array based direction of arrival (DoA) estimation technique that exploits eigen structure of input data matrix. It can be implemented to provide asymptotically unbiased estimates of number of signals, DoA’s and polarizations. In this thesis, MUSIC is used by incorporating polarimetry to separate the scattering centers associated with ground and vegetation components in polarimetric SAR interferometry (Pol-InSAR) measurements. The sensitivity of the MUSIC algorithm to noise and vegetation level is investigated using simulated data. Simulations shows that the probability of detection of the vegetation component decreases with decreasing SNR and vegetation level. Furthermore, the error in the estimate of the ground component increases with an increase in vegetation level due to higher vegetation bias. The MUSIC algorithm is also verified by using L-band Pol-InSAR field measurements from Glenn Affric region.
NOTE: All ECE Graduate Students are ENCOURAGED to attend.
All interested parties are invited to attend. Open to the public.
Advisor: Dr. Dayalan P. Kasilingam
Committee Members: Dr. John R. Buck and Dr. Karen L. Payton, Department of Electrical & Computer Engineering
LOCATION: Lester W. Cory Conference Room, Science & Engineering Building (SENG), Room 213A
ABSTRACT:
Interferometric Synthetic Aperture Radar (InSAR) is used to generate Digital Elevation Map (DEM) from multiple high resolution SAR images. The phase values of the complex reflection images are used to yield scattering phase center (SPC) which is then used to extract elevation information for each pixel of an image. Interferometry assumes that the return from a pixel can be associated with a single SPC at a fixed elevation. This is not the case for forested terrain as elevation of vegetation and elevation of ground results in two SPCs leading to errors in DEM estimates of the terrain. Fully polarimetric SAR (PolSAR) measurements have the potential to separate different scattering mechanisms based on their polarimetric signatures. The multiple signal classification (MUSIC) algorithm is an array based direction of arrival (DoA) estimation technique that exploits eigen structure of input data matrix. It can be implemented to provide asymptotically unbiased estimates of number of signals, DoA’s and polarizations. In this thesis, MUSIC is used by incorporating polarimetry to separate the scattering centers associated with ground and vegetation components in polarimetric SAR interferometry (Pol-InSAR) measurements. The sensitivity of the MUSIC algorithm to noise and vegetation level is investigated using simulated data. Simulations shows that the probability of detection of the vegetation component decreases with decreasing SNR and vegetation level. Furthermore, the error in the estimate of the ground component increases with an increase in vegetation level due to higher vegetation bias. The MUSIC algorithm is also verified by using L-band Pol-InSAR field measurements from Glenn Affric region.
NOTE: All ECE Graduate Students are ENCOURAGED to attend.
All interested parties are invited to attend. Open to the public.
Advisor: Dr. Dayalan P. Kasilingam
Committee Members: Dr. John R. Buck and Dr. Karen L. Payton, Department of Electrical & Computer Engineering
Contact:
ECE: Electrical & Computer Engineering Department 508.999.9164 http://www.umassd.edu/engineering/ece/
Topical Areas: General Public, University Community, College of Engineering, Electrical and Computer Engineering