变步长LMS自适应极化递推估值算法

Adaptive recursive-estimation algorithm of polarization domain based on variable step-size LMS

为了解决最小均方误差算法(least mean square,LMS)在干扰极化状态估值中存在的收敛速度和稳态误差之间的矛盾,应用变步长LMS算法进行干扰的极化状态递推估值。分析了传统定步长因子μ的选取和其对算法达到稳态时误差的影响;讨论了当干扰极化状态变化时算法的跟踪性能;并以雷达测角为例,进一步分析算法的实际应用可行性。最后给出了算法实现的原理方案。仿真结果和理论分析相一致,证明了该方法的有效性。

In order to solve the contradiction between the convergence speed and the steady-state errors of LMS algorithm, variable step size LMS algorithm is applied to estimate interference＇ s polarization parameters adaptively. The choice of traditional step parameter μ and its effect on steady-state errors are analyzed. The algorithm＇s tracking performance is discussed when the polarization parameters of interference varies timely. Furthermore, radar angle measurement is taken as an example to analyze the feasibility of the algorithm＇ s practical application and the realization principle scheme of the algorithm is presented. The simulation results show that the method is effective.