基于改进GA的周期长码直扩信号PN码估计

Improved GA Based PN Code Estimation of Long Period Code DSSS Signals

针对周期长码直接扩频信号的PN码盲估计问题,提出了一种基于改进GA的扩频码估计方法。首先,通过观测信号来初始化种群,在种群更新时保留最优个体并加入一部分随机产生的个体防止局部最优的方法来改进GA;然后,根据信号协方差矩阵的谱范数来估计PN码与信息码的同步点;最后,截取一周期的观测信号,利用改进的GA来估计PN码。仿真结果表明,改进后的算法加快了收敛速度,减少了迭代次数,在低信噪比条件下能够取得良好的效果。

Aiming at the problem of blind PN code estimation of long period code Direct Sequence Spread Spectrum(DSSS)signals a spread spectrum code estimation method based on improved Genetic Algorithm(GA)is proposed.Firstly the GA is improved by initializing the population with observation signals retaining the optimal individuals and adding some randomly generated individuals to prevent local optimization.Then the synchronization point of PN code and information code is estimated according to the spectral norm of signal covariance matrix.Finally a period of observation signal is intercepted and the improved GA is used to estimate the PN code.The simulation results show that the improved algorithm speeds up the convergence process reduces the number of iterations and achieves good results under the condition of low SNR.