基于内插型双边带滤波器的时域自适应滤波

针对过采样条件下直接序列扩频（DSSS）系统中采样样值相关性造成在使用传统时域自适应滤波窄带干扰抑制方法时扩频信号失真的问题，提出一种改进的时域自适应滤波方法.该方法基于内插型双边带滤波器，采用抽取-内插结构，结合最小均方（LMS）算法进行自适应权值更新，实现窄带干扰抑制.理论分析和仿真结果表明，在高信噪比情况下，该方法与常规自适应滤波方法比较，具有更小的信噪比回退和有用信号畸变；同时低信噪比情况下，其误码率性能也略有优势. 

Time-Domain Adaptive Filtering Algorithms Based on Interpolating Transversal Filter with Two-Sided Taps

In order to solve the problem of spread spectrum signal distortion caused by raised correlation between the samples with general time-domain adaptive filtering narrowband interference suppression method in the oversampling direct sequence spread spectrum (DSSS) system, an improved time-domain adaptive filtering algorithm was proposed based on interpolating transversal filter with two-sided taps and the minimum mean square (LMS) algorithm to update the weights adaptively. Combined with downsample-upsample structure, it could effectively suppress narrowband interference. Both theoretical analysis and simulations show that, compared with traditional adaptive filter method, the proposed algorithm can not only lower signal-to-noise ratio (SNR) loss, but also get excellent characteristics as small distortion of desired signal in high SNR conditions, meanwhile it has a slight advantage in bit error rate(BER) performance in the low SNR conditions.