基于相似度的直扩信号盲解扩方法

Similarity based blind despread method of DS-SS signal

针对传统方法对直扩(direct sequence spread spectrum,DS-SS)信号进行盲解扩时,需要在估计出扩频序列后,才能完成信号盲解扩的问题,提出了一种基于相似度的DS-SS信号盲解扩方法。该方法首先在扩频码的码片速率和周期已知的条件下,以单倍扩频码周期的窗长对接收信号进行数据分段,然后对任意两段数据求相似度函数值,构造相似度函数值的特征信息矩阵,最后通过对构造的特征信息矩阵进行特征值分解就可以实现对信息序列及扩频码序列的盲估计。理论推导和仿真实验结果表明,该方法具有精度高、稳定性好,在信噪比容限值为-22dB的条件下也能够有效的盲估计DS-SS信号的信息序列及扩频码序列。

Aiming at the problem of the traditional blind despread method for the direct sequence spread spectrum （DS-SS） signal, which needs to estimate spread spectrum sequence to complete the DS-SS signal blind despreading, a similarity based blind despread approach of DS-SS signal is proposed to solve the problem. Some parameters of DS-SS signals need to be known. Firstly, the received signal is divided into continuous non-over-lapping temporal vectors according to one period of spread spectrum sequence, then their feature information matrix of similarity function value is constructed by calculating similarity function value of these vectors one by one. Finally, eigen value decomposition （EVD） is applied to the feature information matrix, and the blind esti-mation of the information sequence is obtained based on EVD. Theoretical analysis and simulation results show that the proposed method has high accuracy and good stability, which can effectively estimate the information sequence and spread spectrum sequence of the DS-SS signals under the condition of signal-to-noise ratio （SNR） is -22 dB.