在这项研究中，我们介绍了两种基于分数低阶循环平稳性的鲁棒信号选择新算法，以解决在存在干扰和α稳定分布脉冲的情况下估计循环平稳信号到达时间差（TDOA）的问题噪音。 基于传统的信号选择和分数低阶统计量（FLOS）的TDOA方法在存在非高斯α稳定脉冲噪声和干扰信号干扰的情况下会导致性能下降。 通过利用分数低阶循环平稳性，我们能够开发一种新颖的多周期方法和广义分数阶低阶光谱相干方法。 所提出的方法抑制了α稳定脉冲噪声的影响，并更好地利用了循环平稳信号的循环平稳特性。 仿真结果表明，新方法对干扰和脉冲噪声具有较高的容忍度，并且比常规算法具有更高的估计精度。

Direction of Arrival Estimation for Coherently Distributed Sources in 2D Massive MIMO Systems

Classical and Modern Direction-of-Arrival Estimation

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