基于环路滤波器的低复杂度LMS算法设计

研究利用多天线结构对测控信号内存在的干扰进行对消和信号增强的技术。首先介绍传统空域干扰对消算法LMS，以及LMS的诸多改进算法，分析当前这些LMS算法在强干扰存在时收敛稳定性和收敛速度之间的折中关系以及参数调节的难度，分析了定步长和变步长LMS算法的优劣。针对变步长LMS由于动态环境以及大功率干扰的存在引起的收敛速度变慢和步长计算复杂的问题，提出了一种基于二阶环路滤波器累计误差的低复杂度LMS算法LF-LMS，该算法弱化单次误差的不稳定性并提高累计误差的稳定性，利用大步长和可变误差以实现快速收敛并缩小进入稳定状态后的误差波动，且计算量较小，可以有效应用于DSP工程实现，并通过仿真验证了算法在收敛速度和动态环境下的鲁棒性。

A new reduced complexity LMS algorithm based on loop filter

This paper focuses on jamming cancelling and signal enhancement for measurement and control signals based on adaptive beamforming. Firstly, the conventional LMS algorithm and its improved versions are introduced. The tradeoff between the speed of convergence of the LMS algorithm and its residual error floor is described, which causes difficulties in obtaining proper adaptation step size. To solve the computation complexity and low speed of convergence in dynamic communication environment, a new reduced complexity LMS algorithm based on second-order loop filter (LF-LMS) is proposed. The new algorithm improves the reliability of the adaptive beamforming array and reduces the error variance of convergence by using proper step size and variable error estimation. The reduced computation complexity can also simplify the realization on DSP platforms. Simulation results demonstrate the effectiveness of our proposed algorithm.