自适应沃尔泰拉均衡器能够有效地均衡卫星信道的非线性失真,但存在收敛速度慢的缺点.将LMS Newton算法应用于自适应沃尔泰拉均衡中,提出了快速非线性Shrinkage LMS Newton均衡算法.该算法通过使用Shrinkage方法和L1-L2范数最小化公式获得了噪声自由的先验误差与后验误差,再利用噪声自由的后验误差能量最小化的方法推导了一种最佳的变步长收敛因子,有效地提高了算法的收敛速度.仿真结果表明,Shrinkage LMS Newton均衡算法能够有效地纠正信号的幅度失真和相位失真,解决了卫星信道非线性失真的问题,并且与传统算法相比,Shrinkage LMS Newton算法在几乎不增加计算复杂性的基础上能够获得更快的收敛速度. The adaptive Volterra equalizer can effectively balance the nonlinear distortion of the satellite channel, but has the disadvantage of slow convergence rate.When LMS Newton algorithm is applied to adaptive Volterra equalization, a fast and nonlinear Shrinkage LMS Newton Equalization algorithm.The algorithm obtains the a priori error and the posterior error of noise freedom by using the Shrinkage method and the L1-L2 norm minimization formula, and then uses the method of minimizing the posterior error energy of noise freedom to derive a best Which can effectively improve the convergence rate of the algorithm.The simulation results show that the Shrinkage LMS Newton equalization algorithm can effectively correct the amplitude and phase distortion of the signal and solve the problem of nonlinear distortion of the satellite channel, Compared with the algorithm, the Shrinkage LMS Newton algorithm can achieve faster convergence speed with almost no increase of computational complexity.