反卷积波束锐化改进算法

Improved Deconvolution Beamforming Sharpening Algorithm

反卷积波束形成方法近年来在波束形成系统中得到了应用,Richardson-Lucy算法在有效计算反卷积问题时还存在随着迭代次数增加噪声随之放大的问题,论文通过将Richardson-Lucy算法与全变分正则化相结合,提出了全变分正则化R-L方法,新方法求解了带全变分正则项的Richardson-Lucy模型,并使用仿真数据和试验进行了测试,取得了良好的锐化效果,并提升了噪声抑制能力。

The deconvolution beamforming method has been applied in beamforming systems in recent years.However,the Richardson Lucy algorithm still faces the problem of noise amplification as the number of iterations increases when effectively calculating deconvolution problems.This article proposes a total variation regularization R-L method by combining Richardson Lucy algorithm with total variation regularization.The new method solves the Richardson Lucy model with total variation regularization term and tests it using simulation data and experiments,achieving good sharpening effect and improving noise suppression ability.