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Fast method for spreading sequence estimation of DSSS signal based on maximum likelihood function

机译:基于最大似然函数的DSSS信号扩频序列估计的快速方法

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摘要

To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. By simplifying the objective function of maximum likelihood estimation, the algorithm can realize sequence synchronization and sequence estimation via adaptive iteration and sliding window. Since it avoids the correlation matrix computation, the algorithm significantly reduces the storage requirement and the computation complexity. Simulations show that it is a fast convergent algorithm, and can perform well in low signal to noise ratio (SNR).
机译:为了估计直接序列扩频(DSSS)信号的扩频序列,提出了一种基于最大似然函数的快速算法,并提供了该算法的理论推导。通过简化最大似然估计的目标函数,该算法可以通过自适应迭代和滑动窗口实现序列同步和序列估计。由于避免了相关矩阵的计算,该算法大大降低了存储需求和计算复杂度。仿真表明,该算法是一种快速收敛的算法,在低信噪比(SNR)下性能良好。

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