非周期长码直扩信号同步及伪码序列盲估计

非合作直接序列扩频系统中伪随机码的估计与同步是正确获取信息的关键。现有的研究成果多集中在短码或周期长码直扩信号的解扩，该文针对无伪码先验知识条件下NPLC-DSSS信号的失步时间估计问题，提出一种基于相关矩阵元素分布建模的方法，该方法以信息码宽分段的信号构建自相关矩阵，并以该矩阵的Frobenius 范数与失步时间之间的对应关系，实现NPLC-DSSS信号失步时间的精确估计。在此基础上，通过引入判决辅助思想构建了循环迭代结构实现了NPLC-DSSS信号伪码序列的盲估计。最后，推导了该伪码序列盲估计问题的Cramer-Rao理论界。数值分析结果表明，文中所述算法在相同的信噪比和数据量条件下具有更好的估计精度，且对伪码的估计性能接近理论界。

Blind Synchronization and Estimation for PN Code of NPLC-DSSS Signal

Synchronization and estimation for Pseudo Noise (PN) code of non-cooperative Direct Sequence Spread Spectrum(DSSS)system is the key to obtain the information correctly. Previous works mostly concentrate on Short or Periodic Long Code DSSS(SC-DSSS, PLC-DSSS)signal. Aiming at the estimation for out-of-step time of Non-Periodic Long Code DSSS (NPLC-DSSS) signal without the prior knowledge about the PN code, a distribution modeling-based method for the elements of correlation matrix is proposed. The auto-correlation matrix of information-bit-long segments is constructed and the accurate estimation for out-of-step time is achieved according to the Frobenius norm as a function of out-of-step time. On this basis, by introducing decision aided idea, the cyclic iterative structure is constructed to realize a blind estimation for PN sequence of NPLC-DSSS signal. Finally, the Cramer-Rao Bound (CRB) for the blind PN code estimation problem is derived. Numerical analysis results demonstrate that the proposed method can achieve better estimation accuracy in the same signal to noise ratio and data volume condition and the performance is close to the theoretical bound.