改进的抗窄带干扰非线性预测方法

为了有效抑制直接序列扩频通信中的窄带干扰，提出了2种改进的非线性预测方法（NLMSN和LNLMSN）。NLMSN是在原非线性预测方法的基础上，针对NLMS算法在强干扰条件下抑制性能不理想的缺点，运用修正LMS Newton算法对其进行改进而得到的方法。LNLMSN是在NLMSN的基础上，引入Laguerre时延单元，使得这两种方法在取得相同信噪比改善量的同时，减少了滤波器阶数，降低了方法实现的复杂度。仿真结果表明，与原方法相比，改进方法的抗干扰性能有了较大提高。

Improved Nonlinear Prediction Methods for Narrow-band Interference Rejection

Two improved nonlinear prediction methods are proposed to effectively suppress narrowband interference in Direct Sequence Spread Spectrum（DSSS）, namely NLMSN and LNEMSN. Aiming at the fact that the performance of suppressing strong interference for the NLMS algorithm is not perfect, NLMSN is proposed by applying the modified LMS Newton algorithm to improve the former nonlinear prediction method. Based on NLMSN, LNLMSN is put forward by introducing Laguerre memory structure. Simulation results indicate that both NLMSN and LNLMSN have the same performance and are implemented easily in engineering. These two nonlinear prediction methods exceed conventional ones at suppressing narrow-band interference.