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Robust adaptive DOA estimation method in an impulsive noise environment considering coherently distributed sources

机译:考虑相干分布源的脉冲噪声环境下的鲁棒自适应DOA估计方法

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Many approaches have been studied for the direction of arrival (DOA) estimation of distributed sources under additive Gaussian noise environments, but these schemes typically perform poorly when the noise is modeled as an alpha-stable distribution. This paper extends the definition of correntropy, which exhibits a robust statistical property under impulsive noise environments, by proposing a novel generalized autocorrentropy (GCO) operator. To improve the performance of the GCO operator, an adaptive kernel size function is deduced for symmetric alpha-stable (S alpha S) distributed random variables. Since the adaptive kernel size function does not require any empirical parameter of the impinging signals, it is particularly suitable for cases of practical interest. Based on the advantage of the GCO operator, a distributed signal parameter estimator (DSPE)-like algorithm is proposed for the DOA estimation of coherently distributed (CD) sources in the presence of impulsive noise. Comprehensive simulation results show that the proposed algorithm surpasses the existing algorithms concerning estimation accuracy and probability of resolution under the S alpha S distributed impulsive noise environments. We also conduct comparisons with the existing DOA estimation algorithms under the other two typical impulsive noise conditions. (C) 2019 Elsevier B.V. All rights reserved.
机译:对于加性高斯噪声环境下的分布式源的到达方向(DOA)估计,已经研究了许多方法,但是当将噪声建模为α稳定分布时,这些方案通常效果较差。本文通过提出一种新型的广义自体熵(GCO)算子,扩展了对熵的定义,该定义在脉冲噪声环境下表现出强大的统计特性。为了提高GCO运算符的性能,针对对称的α稳定(S alpha S)分布随机变量推导了自适应核大小函数。由于自适应核大小函数不需要撞击信号的任何经验参数,因此它特别适合于实际需要的情况。基于GCO算子的优势,提出了一种类似脉冲信号估计器(DSPE)的算法,用于在存在脉冲噪声的情况下对相干分布(CD)源进行DOA估计。综合仿真结果表明,在S alpha S分布脉冲噪声环境下,该算法在估计精度和分辨率概率方面均优于现有算法。我们还与其他两种典型的脉冲噪声条件下的现有DOA估计算法进行了比较。 (C)2019 Elsevier B.V.保留所有权利。

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