Title :
Signal decomposition for wind turbine clutter mitigation
Author :
Uysal, Faruk ; Pillai, Unnikrishna ; Selesnick, Ivan ; Himed, Braham
Author_Institution :
C&P Technol. Inc., Closter, NJ, USA
Abstract :
This paper addresses the problem of dynamic clutter mitigation by focusing on the mitigation of the wind turbine clutter from the radar data. The basis pursuit and morphological component analysis approach are used to decompose the radar returns into the sum of oscillatory and transient components. The success of the morphological component analysis rely on sparsity, thus different transform domains needs to be identified correctly to represent each component sparsely. The method is illustrated on a radar data collected from a small custom built radar system to show the success of the proposed algorithm for wind turbine clutter mitigation.
Keywords :
compressed sensing; mathematical morphology; radar; radar clutter; signal reconstruction; signal representation; wind turbines; morphological component analysis; radar data; radar system; signal decomposition; wind turbine clutter mitigation; Blades; Clutter; Doppler radar; Mathematical model; Radar imaging; Wind turbines; Signal decomposition; sparse signal representation; wind turbine clutter mitigation;
Conference_Titel :
Radar Conference, 2014 IEEE
Conference_Location :
Cincinnati, OH
Print_ISBN :
978-1-4799-2034-1
DOI :
10.1109/RADAR.2014.6875555