摘要
本文分析了直接序列扩频(DSSS)系统中最小错误概率(MPE)意义下的最优滤波器,并依据矩阵求逆引理证明最小均方误差(MMSE)意义下的最优滤波——维纳滤波也是MPE意义下的最优滤波。在DSSS中应用自适应滤波,无须先验已知扩频码的码型和干扰的统计特性,就能一并完成解扩以及有效抑制干扰。离散傅立叶变换/最小均方(DFT/LMS)算法的收敛速度远快于LMS算法,而运算量、稳健性与LMS算法基本相同。基于DFT/LMS算法的自适应滤波大大简化DSSS系统接收机的设计,显著增强系统抗干扰能力,具有很强的实用性。
This paper analyzes the optimum filter optimized in the minimum probabil-ty of erro (MPE) sense in direct
sequence spread spectrum (DSSS), then proves that, using matrix inversion lemma, the Wiener filter optimized in the minimum
mean square error (MMSE) sense is also the optimum filter in the MPE sense. Applying the adaptive filter in DSSS, despreading
and suppressing interfrence can be done simultaneously without prior knowledge of the pseudonoise code and the statistical
characterization of the interference. The discret fourier transform / least mean square (DFT/LMS) algorithm has significantly
improved convergence speed over the least mean square (LMS) algorithm, and meanwhile the complexities and robust
performance of the two algorithms are almost identical. Since the adaptive filter using the DFT/LMS algorithm significantly
simplifies the design of the receiver, and notably enhances the capability of the anti-interference, it is of good practicability.
出处
《信号处理》
CSCD
2004年第3期322-325,289,共5页
Journal of Signal Processing
基金
JS63空间微波技术国防科技重点室基金(项目编号:2000JS63.3.1.KG0111)
关键词
DSSS
DFT算法
LMS算法
性能分析
直接序列扩频系统
direct sequence spread spectrum(DSSS)
minimum probability of error(MPE)
interference suppression
discret fourier transform/least mean square (DFT/LMS) algorithm