一种抑制直扩通信窄带干扰的新型非线性自适应预测滤波器

A Novel Nonlinear Adaptive Prediction Filter for Narrowband Interference Suppression in DS-SS Communication

为了更有效地抑制直接序列扩频通信中的窄带干扰，论文提出了一种非线性Laguerre滤波抑制直扩频通信窄带干扰的方法，给出相应的自适应算法。该方法利用具有IIR和FIR滤波器特点的Laguerre时延单元构造非线性自适应预测滤波器。该方法可以使预测器的记忆深度与预测器的阶数解偶，以更少的阶数达到更优的抑制性能。仿真实验结果表明：与Vijayan和Poor传统非线性自适应预测滤波器相比，该滤波器能够保证均方误差的收敛稳定性，并能在信噪比改善提高1-2dB的前提下，使滤波器阶数降低为原来的1／3～1／5，具有一定的现实意义。

A novel nonlinear adaptive prediction approach based on truncated Laguerre memory structure is proposed to effectively suppress NarrowBand Interference （NBI） in Direct Sequence Spread Spectrum （DSSS）. The memory depth can be uncoupled with the filter orders. Simulation results show that the proposed nonlinear adaptive prediction scheme outperforms the other exiting nonlinear adaptive prediction methods for the NBI suppression in DSSS, and the orders of the proposed filter can be largely reduced 3-5 times than that of Vijayan and Poor＇s filters.