基于二阶Volterra级数滤波器的海杂波建模研究

Sea Clutter Modeling Based on Second Order Volterra Series Filter

讨论了运用二阶Volterra级数滤波器进行海杂波建模预测的方法。根据相空间重构理论,以海杂波序列的嵌入维数作为滤波器长度,建立了二阶截断的Volterrra滤波器并行的乘积耦合实现结构,降低了滤波器的应用复杂程度。采用了一种自适应调整的NLMS算法实时调整滤波器系数,对比试验表明该算法具有更快的收敛速度和更小的均方误差。用Volterra级数滤波器对真实海杂波数据进行了预测分析,结果表明该模型能够准确地预测海杂波,虽然在一步预测误差性能上稍逊于RBF网络,但在较大步长时性能占优。

The method for sea clutter modeling with second order Volterra series filter is discussed.According to the phase space reconstruction theory,the embedded dimension is adopted as the length of the filter. The parallel multiplication-coupled structure for second order Volterra series filter is built up to reduce the complexity. The adaptive NLMS algorithm is used for adjusting the filter core coefficient in real time.Contrast experiment shows that the algorithm has faster convergence rate and smaller MSE. The Volterra filter was used for prediction of real sea clutter data. The results indicate that： 1） this filter can model and predict sea clutter accurately; and 2） compared with RBF network,it has better performance for large step prediction,while it is slightly inferior in one-step prediction performance.