SAR Imaging Based on Multiple Measurements Vectors Bayesian Compressed Sensing
LI Qiangyun
WU Xinwei
Abstract：Synthetic aperture radar imaging based on compressed sensing could reduce the number of data ,enhance res-olution ratios and cut down the bandwidth of signals .As the procedures of imaging are disturbed by noises and clutters ,the results of SAR imaging is not very well in low SCNR .Multiple measurements vectors Bayesian algorithm ,a new strategy a-bout SAR imaging on the base of CS theory was proposed in this paper ,which can reduce the sampling frequency by CS theo-ry in rang direction and extract randomly aperture positions to send and receive signals in azimuth direction .Using the least apertures and sampling data to reconstruct the targets scattering coefficients as it possible .The paper validates that the re-sults of SAR imaging on the base of multiple measurements vectors Bayesian algorithm are more sharp-pointed than tradition-al CS algorithms ,sparser and higher resolutions than single measurements vectors Bayesian algorithm by simulating experi-ments on simple targets and complicated 2D imaging .
Keywords：synthetic aperture radarcompressed sensingmultiple measurements vectorsBayesian compressed sensing
Publication Date：2015-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 1403-1408 )