Abstract: Efficient imaging algorithm is one of the key technologies of synthetic aperture microwave radiometer. Since the inverse problem of synthetic aperture microwave radiometer is mathematically ill-posed, it needs to be regularized to overcome its ill conditioned properties and provide a unique and stable solution. Compared with the direct regularization method, the Conjugate Gradient Least Squares (CGLS) iterative algorithm has several advantages on solving inverse problem: both the explicit regularization parameter and inversion of the transfer matrix are not required. It is proposed that the CGLS algorithm is applied to the imaging of synthetic aperture radiometer, and its performance is compared with the classical minimum norm regularization based on the Full Polarization Interferometric Radiometer (FPIR) system. The simulation results show that the CGLS regularization algorithm can effectively reduce the reconstruction error in the FPIR system, compared with minimum norm regularization. The CGLS regularization algorithm can obtain more accurately the brightness temperature distribution of the scene under observation in order to meet application requirement of detecting wind field of the ocean surface, sea surface salinity, soil moisture and so on.