摘要
作为一种梯度自适应波束形成算法,LMS算法因简单有效而得到广泛的应用。但是在存在偏差的情况下,LMS算法的性能较差。针对上述问题,考虑信号方向向量的偏差对LMS算法性能的影响,提出了一种基于对角载入的鲁棒约束LMS算法,并对算法的对角载入因子和收敛性能进行了分析,给出了保证算法收敛的步长取值范围。该算法利用对角载入的特性,可有效的抑制各种偏差所带来的影响,收敛速度快,抗扰动性强,对信号方向向量的偏差具有较强的鲁棒性,从而可以保证阵列输出的信干噪比接近最优值。仿真实验表明,与传统约束LMS算法相比,基于对角载入的鲁棒自适应波束形成算法具有很好的性能。
LMS algorithm is simple and effective as adaptive beamforming algorithms, but its performance is known to degrade substantially in the presence of even slight mismatches between the actual and presumed array responses to the desired signal. In order to overcome the shortage, a novel approach to robust adaptive beamforming based on diagonal loading was proposed. The diagonal loading factor and convergence performance were analyzed and the convergence scope of robust constrained LMS （RCLMS） algorithm was also given. The proposed RCLMS algorithm based on diagonal loading offers faster convergence rate, provides excellent robustness against the signal steering vector mismatches and makes the mean output array SINR consistently close to the optimal one. Computer simulation results support the analysis and compare the performance of the proposed algorithm with the traditional constrained-LMS algorithm.
出处
《系统仿真学报》
EI
CAS
CSCD
北大核心
2007年第12期2786-2789,共4页
Journal of System Simulation
基金
教育部博士点基金资助项目(20050145019)
关键词
鲁棒自适应算法
信干噪比
LMS算法
对角载入
robust adaptive beamforming algorithm
signal-to-interference-plus-noise ratio （SINR）
LMS algorithm
diagonal loading
