基于改进传播算子的DS-SS信号扩频序列盲估计方法

Blind Estimation of the Spread Spectrum Sequence of DS-SS Signals Based on Improved Propagator Method

本文研究了DS-SS信号的扩频序列盲估计问题,针对现有特征值分解算法失步时间估计不准和计算量大等缺点,提出一种基于改进传播算子的扩频序列盲估计算法,该算法对传统传播算子估计信号子空间的方法进行了改进,使之能够估计扩频序列,并利用信号子空间估计信号失步时间.与基于特征值分解的方法相比,本文算法提高了失步时间的估计精度,并有效的降低了计算量.最后对算法计算量和性能进行了仿真分析和验证,结果表明本文算法有效,计算量远小于现有特征值分解算法,且估计性能在低信噪比条件下更优.

Aiming at the problem of inaccurate estimation of out-of-step time and large computation in eigenvalue decomposition algorithm,the direct sequence spread spectrum(DS-SS) signal blind estimation problem of spread spectrum sequence is studied,and an algorithm based on improved propagator is proposed in this paper.The algorithm can estimate the spread spectrum sequence and the signal out-of-step time by using the signal subspace.Compared with the eigenvalue decomposition method,the estimation accuracy of the out-of-step time is improved and the amount of calculation is effectively reduced.Finally,the computational amount and performance of the algorithm are simulated and verified.The results show that the proposed algorithm is effective,the computational amount is far less than the eigenvalue decomposition algorithm,and the performance is better under the condition of low SNR.