基于奇异值分解的直扩信号伪码序列及信息序列盲估计方法

Blind Estimation of the PN Sequence and Information Sequence of a DSSS Signal Based on SVD

针对非合作扩频通信中直扩信号伪码序列的盲估计问题,在已知码片速率和伪码周期的前提下,该文提出一种基于奇异值分解的直扩信号伪码序列及信息序列的盲估计方法。该方法对接收信号构成的观测矩阵进行奇异值分解,通过左奇异向量实现伪码序列估计的盲估计。同时,通过右奇异向量可以在信号序列未同步和伪码序列未知的情况下实现信息序列的盲估计。仿真实验结果表明该算法具有精确度高、稳定性高、计算量小和观测时间短等优点。

With focus on blind estimation of the Pseudo-Noise （PN） sequence of a Direct Sequence Spread Spectrum （DSSS） signal in non-cooperative spread spectrum communications, a blind estimation approach of PN sequence and information sequence is proposed based on Singular Value Decomposition （SVD）. The chip rate of the PN sequence and the PN sequence period need to be known. Firstly, SVD is applied to the signal observation matrix made up of received signal. Then, the estimation of the PN sequence is obtained based on the left singular vector. At the same time, the information sequences can be estimated with the signal sequence unsynchronized and the PN sequence unknown through the right singular vector. Simulation experiment results verify that the proposed approach is of high stability, high accuracy, low computational complexity and short observation time.