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中文摘要：
提出了一类适用于Alpha稳定分布随机变量的统计量—类M估计相关（MELC）,通过构造阵列输出的类M估计相关矩阵,提出了适用于Alpha稳定分布噪声环境下的波达方向（DOA）估计新算法,即MELC-MUSIC算法。仿真实验表明,在Alpha稳定分布噪声环境下,MELC-MUSIC算法在抗噪声特性、多源信号分辨性以及对不同形式信号（圆对称信号或非圆对称信号）的适应性方面获得比基于分数低阶统计量（FLOS）的MUSIC方法更好的估计性能。
英文摘要：
A novel class of bounded statistics, namely, the M-estimate like correlation （MELC） for independently identi- cal distributed symmetric alpha-stable （ SaS ） random variables was defined. Based on the MELC matrix for the array sensor outputs, a new algorithm for direction of arrival （DOA） estimation in the presence of complex SaS noise was proposed. The comprehensive Monte-Carlo simulation results show that the MELC-MUSIC algorithm not only outper- forms the fractional lower order statistics （FLOS） based MUSIC algorithms under low SNR conditions and multi-source signals environment, but also is robust with circular and noncircular signals.
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