Techniques to improve the CLEAN deconvolution algorithm

The CLEAN algorithm was introduced in radio astronomy as a means to overcome the shadowing of small targets by the sidelobes of the point spread function (PSF) of a strong target. The idea was further used in microwave imaging where the concept of coherent CLEAN was introduced. The classical CLEAN algorithm is limited to a case where the targets are isolated. Techniques to overcome this limitation are presented in this paper. These techniques include PSF correlation to improve the estimation of target locations and intensities, sequence CLEAN (S-CLEAN) which improves the detection of true targets and suppresses the detection of false ones, and iterative CLEAN (ICLEAN) which uses knowledge about a target to improve the estimation of other targetsʹ parameters. Emulation, using real experimental data, shows that a significant improvement can be achieved using these techniques.