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DOA Estimation of Uncorrelated, Partly Correlated and Coherent Signals Using Alternating Oblique Projection

机译:使用交替倾斜投影的不相关,部分相关和相干信号的DOA估计

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The problem of direction-of-arrival (DOA) estimation is important in array signal processing. To estimate the DOAs of uncorrelated, partly correlated and coherent signals, a new iterative DOA estimation algorithm, named AOP-DOA, is proposed by using alternating oblique projection (AOP). In each iteration, the oblique projection approach is employed to separate the received signals, then the DOA of each separated signal is estimated one after another. After theoretical analysis on the relationship between the proposed AOP-DOA and the conventional alternating projection based maximum likelihood estimator (AP-MLE), an AOP&AP-DOA algorithm, which is a combination of AOP-DOA and AP-MLE, is developed to reduce the computational complexity of AOP-DOA. Extensive experiments validate the effectiveness and complexity of the proposed two algorithms. Particularly, AOP&AP-DOA keeps the merits of AOP-DOA, but exhibits superiority over AOP-DOA in terms of computational complexity when proper adaptive grid refinement strategy is applied.
机译:到达方向(DOA)估计的问题在阵列信号处理中很重要。为了估计不相关,部分相关和相干信号的DOA,提出了一种新的迭代DOA估计算法,称为AOP-DOA,它使用交替斜投影(AOP)。在每次迭代中,采用倾斜投影方法来分离接收到的信号,然后逐个估计每个分离信号的DOA。在对所提出的AOP-DOA与传统的基于交替投影的最大似然估计器(AP-MLE)之间的关系进行理论分析之后,开发了一种AOP&AP-DOA算法,该算法是AOP-DOA和AP-MLE的组合,可减少AOP-DOA的计算复杂度。大量实验验证了所提出的两种算法的有效性和复杂性。特别是,AOP&AP-DOA保留了AOP-DOA的优点,但在采用适当的自适应网格细化策略时,在计算复杂度方面却优于AOP-DOA。

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