شماره ركورد كنفرانس :
3926
عنوان مقاله :
Block Compressive Sensing in Synthetic Aperture Radar (SAR)
پديدآورندگان :
Kazemi Peyman peyman.kazemi@ec.iut.ac.ir Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan, Iran, 84156-83111 , Modarres-Hashemi Mahmood modarres@cc.iut.ac.ir Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan, Iran, 84156-83111 , Naghsh Mohammad Mahdi mm_naghsh@cc.iut.ac.ir Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan, Iran, 84156-83111
كليدواژه :
Synthetic Aperture Radar (SAR) , Compressive Sensing (CS) , Block Compressive Sensing (BCS) , Sparsity , Imaging.
عنوان كنفرانس :
بيست و چهارمين كنفرانس مهندسي برق ايران
چكيده فارسي :
High rate A/D’s, heavy computations, large on board memories and downlink throughput are serious problems of high resolution Synthetic Aperture Radar (SAR). Compressive Sensing (CS) theory states that the sparsity or compressibility of a signal makes it possible to reconstruct the signal from a reduced number of samples. In the current paper, the Block Compressive sensing (BCS) is applied to SAR. This work proposes a new framework for SAR imaging in which a reconstruction method called BCS algorithm is used to achieve an excellent resolution with a few number of samples. The suggested technique can reconstruct images well by using nearly 1/3 samples in comparison with other CS image reconstruction methods.
