Compressive SAR raw data with principal component analysis
College of Physical and Electronic Information, Tianjin Normal University, Tianjin, China
EURASIP Journal on Wireless Communications and Networking 2012, 2012:258 doi:10.1186/1687-1499-2012-258Published: 16 August 2012
The theory of synthetic aperture radar (SAR) signal model is briefly introduced which is constructed with a series of echo signals in range direction. The procedure of principal component analysis (PCA) is presented which is used as transformation basis to sparsify the signals. The joint compressive sensing (CS) and PCA algorithm is devised to realize SAR raw data compressive measurement. A SAR raw data for a point target is simulated and used to verify the performance of the joint CS and PCA algorithm. The numerical experimental results demonstrate that the PCA method has good sparse performance and the joint CS and PCA algorithm is possible to online compressively measure the SAR raw data.