短码、周期长码直扩信号伪码序列盲估计

针对短码、周期长码直扩信号在不同的时延下伪码序列估计问题，提出了一种基于奇异值分解的盲解扩算法。在已知信息码元速率和伪码周期条件的前提下，算法首先把接收到的直扩信号按照一定长度进行分段构成相关矩阵并对此矩阵进行奇异值分解得出信号子空间，然后根据信号子空间和伪码序列的模糊关系，利用求解的模糊酉矩阵和特定约束条件（如m序列）去其模糊性，最终估计出伪码序列。仿真结果表明，该算法不仅解决了在不同的时延下估计伪码序列带来的问题，而且具有稳定性高、在低信噪比条件下有良好的估计性能等优点。

Blind estimation of PN sequence of short-code and periodic long-code DSSS signals

For the problem of pseudo-noise (PN) sequence estimation of short code and long code direct sequence spread spectrum (DSSS) signals with different delays, a blind despreading algorithm based on singular value decomposition(SVD) is proposed. Under the condition of known information symbol rate and PN period condition, the algorithm first divides the received DSSS signal into a correlation matrix according to a certain length and performs SVD of the matrix to obtain the signal subspace, and then estimates the PN sequence by erasing its ambiguity with the condition of the fuzzy unitary matrix and the specific constraint (such as m sequence) according to the fuzzy relation between the signal subspace and the PN sequence. Simulation results show that the proposed algorithm not only can solve the problem of estimating the PN sequence under different time delays, but also has the advantages of high stability and good estimation performance under low signal-to-noise ratio.