低信噪比下长码直扩信号的符号宽度估计

Symbol Duration Estimation for Long-Code DS-SS Signals under Low SNR

  • 摘要: 针对长码直扩信号,提出了一种新的符号宽度估计算法。在基于高阶自相关统计量和最大化相应的自相关系数中得到粗略估计值,然后基于伪码差分解扩的概念和二阶循环自相关函数得到精确估计值。粗略估计步骤在低信噪比和短数据长度下具有鲁棒性,给精确估计步骤提供一个可信的估计范围,从而改善了精确估计步骤的性能;在精确估计时,采用伪码差分解扩消除伪码序列对循环自相关函数的扰动。仿真表明,和现有方法相比,算法不受伪码限制,同时估计的性能有明显改善,适合于低信噪比下使用。

     

    Abstract: A novel symbol duration estimation for long code direct sequence spectrum spread (DS-SS) signal is proposed. The estimator consists of two steps. Firstly, a coarse estimation is obtained based on a higher-order autocorrelation statistics and maximizing corresponding autocorrelation coefficient. Secondly, based on the principle of differential pseudo-noise (PN) code despreading and second-order cyclic correlation function, a fine estimation is reached. The coarse estimation keeps robust under low signal-noise-ratio (SNR) and small sample size than the fine one, and given the latter a reliable estimation range, so that performance improvement is obtained for the latter. The differential PN despreading is exploited to eliminate the interference effect on the cyclic correlation function by the PN code. Compared with existing theory simulations show that the proposed method is irrelative to the PN codes and obtains significant performance improvement.

     

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