基于SMI—LMS的自适应旁瓣干扰抑制算法研究

摘要

提出基于SMI—LMS的自适应旁瓣干扰抑制算法，即利用采样矩阵求逆（SMI）算法计算初始权值，并以此作为LMS算法的初值。通过比较分析LS-LMS和SMI—LMS的方向图增益和运算量，并运用对角加载技术对SMI-LMS算法作出改进，验证了SMI-LMS算法的优势。仿真实验表明，SMI-LMS算法具有快的收敛速度和低的算法复杂度，在低快拍下有着好的性能。%A new adaptive sidelobe interference suppression forward. Sample Matrix Inversion （SMI） algorithm calculates algorithm. Through comparing the adaptive beam sidelobes and algorithm based on SMI-LMS is put weight vector as initial value for LMS calculating quantity of two algorithms （SMI-LMS and LS-LMS）, and improving the SMI-LMS algorithm by loading method, the SMI-LMS algorithm＇s advantage is approved. Regardless of the interference environments, this algorithm converges to the optimal value with a faster converge speed, and has good performance in low-snapshot data.