改进的SVD算法对BOC信号组合码与信息序列盲估计

针对低信噪比下二进制偏移载波信号的组合码序列以及信息序列盲估计问题,在未知时延下,利用奇异值分解(singular value decomposition,SVD)算法估计出的组合码序列及信息序列,其最大奇异向量和次大奇异向量之间可能存在酉模糊现象。对于该问题的研究,提出一种改进的SVD方法对最大奇异向量及次大奇异向量进行线性组合,接着最优化筛选出其相应的系数矩阵,最后结合系数矩阵估计出组合码序列与信息序列。仿真结果表明,改进的SVD算法可同时应用于组合码和信息序列的估计且不受未知时延的影响,具有消模糊效果好、需要数据量少和抗噪性能强的特点。

Blind estimation of the combination code and the information sequences for BOC signal with improved SVD algorithm

Aiming at blind estimation of the combination code and the information sequences for binary offset carrier signal under low signal-to-noise ratio, the unitary fuzzy phenomenon might exist in the largest singular vector and the secondary largest vector when using singular value decomposition (SVD) algorithm to estimate the combination code and the information sequences under unknown delay. An improved SVD method is proposed to solve this problem. Firstly, the largest singular vector and the secondary largest vector are linearly combined. Then, the coefficient matrix can be selected in an optimal way. Finally, combined with the coefficient matrix, it can estimate the combination code sequence and the information sequence. The simulations show that the improved SVD algorithm can be applied to both the combination code and the information sequences estimation under unknown delay, and it has the characteristics of good unitary fuzzy elimination performance, less data required and strong anti-noise performance.