摘要
直接序列扩频(Direct Sequence Spread Spectrum,DSSS)信号因其良好的保密性、低截获概率、抗干扰性等广泛应用于保密通信。DSSS通信使用一个周期性伪随机序列调制基带信号。不知道该序列的接收者无法解调此信号。论文提出了一种非合作环境下估计扩频序列的方法。该方法基于特征值分解方法,首先将接收信号以符号周期分割为多个不重叠的时间窗,然后设计了一个无偏估计器实现对采样数据的自相关矩阵的无偏估计,最后利用特征值分解方法实现对扩频序列的估计。理论分析和实验结果均表明该方法实现了更低的计算复杂度,具有较强的实时性,且能适应更低的信噪比。
Direct sequence spread spectrum(DSSS)signal is widely used in secure communication because of its good confi⁃dentiality,low probability of interception and anti-jamming.DSSS communication uses a periodic pseudo-random sequence to mod⁃ulate the baseband signal.A receiver which does not know the sequence can not demodulate the signal.This paper proposes a meth⁃od which can estimate the spread spectrum sequence in a non-cooperative environment.The method is based on the eigenvalue de⁃composition(EVD)method.Firstly,the received signal is divided into a number of non-overlapping time windows by symbol peri⁃od,and then an unbiased estimator is designed to realize the unbiased estimation of the autocorrelation matrix of the sampled data.Finally,the EVD method is used to estimate the spread spectrum sequence.Theoretical analysis and experimental results show that the method achieves lower computational complexity and stronger real-time performance.
作者
马超
MA Chao(Naval Research Institute,Beijing 100161;Science and Technology on Complex Ship Systems Simulation Laboratory,Beijing 100161)
出处
《舰船电子工程》
2022年第7期69-74,共6页
Ship Electronic Engineering
关键词
直接序列扩频
特征值分解
无偏估计
扩频序列
自相关矩阵
direct sequence spread spectrum
eigenvalue decomposition
unbiased estimate
spread spectrum sequence
autocorrelation matrix
