基于分数低阶统计量的空域-模糊域DOA估计算法

该文提出一种非高斯SS噪声背景下非平稳信号的DOA估计算法。算法首先定义基于分数低阶统计量的空间模糊函数，利用信号在模糊域中的不同特征将信号分离；然后对不同的信号，选择信号模糊函数对应的模糊点的平均进行子空间分析；最后利用MUSIC算法实现DOA的估计。与基于分数低阶统计量的空域处理方法相比，该文提出的算法利用了信号在模糊域中的信息，提高了算法的估计精度。计算机仿真证明了算法的有效性。

Spatial-Ambiguity-Domain based DOA Estimation Algorithm Using Fractional Lower Order Statistics

In this paper, a DOA estimation algorithm for non-stationary signals embedded in impulsive SαS noise environments is proposed. Firstly, a Spatial Ambiguity Function based on the Fractional Lower Order Statistics (FLOS-SAF) is defined to separate signals by exploiting the ambiguity domain characteristic. Then the average of ambiguity-domain points is carefully selected to perform the subspace analysis. Finally the MUSIC algorithm is applied to obtain DOA estimates. Comparison with the spatial processing method using fractional lower order statistics, the proposed algorithm provides more precise DOA estimates by using the ambiguity domain information of signals. Computer simulation results show the effectiveness of the algorithm.