An Improved DBF Method for Multi-channel SAR Non-uniform Sampling Reconstruction
WANG Aowei
SHANG Mingyang
ZHANG Zhe
Abstract：In azimuth multi-channel Synthetic Aperture Radar(SAR),echo signal reconstruction under non-uniform sampling conditions is highly susceptible to noise amplification,resulting in a degradation of imaging quality.Traditional Digital Beamforming(DBF)methods struggle to effectively suppress noise when the degree of non-uniform sampling increases,as the observation matrix tends to become ill-conditioned.To address this issue,this paper proposes an improved DBF method based on regularization.Specifically,the proposed method imposes regularization constraints on the observation matrix and adaptively adjusts the reconstruction filter to mitigate noise amplification and enhance the signal-to-noise ratio.Furthermore,a regularization parameter adaptation strategy is introduced,allowing the regularization parameter to dynamically adjust according to variations in the sampling pattern.Simulation results demonstrate that,compared to conventional DBF methods,the proposed approach achieves an approximate 6 dB reduction in the azimuth ambiguity-to-signal ratio(AASR)and significantly suppresses noise under realistic data simulation conditions.
Keywords：synthetic aperture radarmulti-channelnon-uniform sampling reconstructionregularization
Publication Date：2025-06-25
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：9( 1-9 )