摘要
在分析线性自适应滤波抑制单频干扰、自回归过程窄带干扰和窄带BPSK调制信号干扰的性能的基础上,提出了一种非线性自适应波抑制方法。在对窄带干扰进行预测前,通过对扩谱信号的估计,使得窄带干扰预测的背景噪声由非高斯转变为高斯,并消除扩谱信号对干扰估计的影响,再通过NLMS和RLS自适应算法进行干扰抑制。理论分析和仿真试验结果表明,这种改进方法对于系统性能的改善效果,明显优于常规自适应滤波抑制方法。
Substantial performance gains can be achieved through the use of active narrowband interference （NBI） suppression prior to despreading and demodulating. This paper proposes a non-linear adaptive filtering method based on analyzing the performance of the conventional adaptive methods in the cases of that the NBI can be modeled as a single tone, an autoregressive （AR） stochastic process or narrow band BPSK digital modulation signals. Before the adaptive filter is employed to remove NBI, we evaluate the spread spectrum signal by maximum post-probability and subtracting from the received signal, which can make back-ground ＂noise＂ become into Gaussian from a non-Gaussian process, so that it can eliminate the impact of the spread spectrum signal on the NBI estimation. Here the adaptive algorithm can be either NLMS or RLS. Theoretical analysis and simulation results show that the modified method behaves much better than the conventional adaptive methods.
出处
《电路与系统学报》
CSCD
北大核心
2008年第1期56-60,共5页
Journal of Circuits and Systems
基金
国家863计划资助项目
关键词
扩谱
窄带干扰
自回归
预测
spread spectrum
narrowband interference
autoregressive
prediction
