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首页> 外文期刊>IEEE Transactions on Signal Processing >Adaptive interference canceler for narrowband and wideband interferences using higher order statistics
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Adaptive interference canceler for narrowband and wideband interferences using higher order statistics

机译:使用高阶统计量的窄带和宽带干扰的自适应干扰消除器

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摘要

A new higher order statistics-based adaptive interference canceler is introduced to mitigate narrowband and wideband interferences in environments where the interference is non-Gaussian and a reference signal, which is highly correlated with the interference, is available. The new scheme uses higher order statistics (HOS) of the primary and reference inputs and employs a gradient-type algorithm for updating the adaptive filter coefficients. The update equation of the HOS-based adaptive filter is independent of uncorrelated Gaussian noises and can mitigate the interference more effectively than adaptive filters based on second-order statistics. The performance of the. HOS-based adaptive filter is much less sensitive to the choice of the step size parameter than the adaptive filters based on the LMS algorithm. It is demonstrated, by means of extensive simulations, that the HOS-based filter can mitigate both narrowband and wideband interferences effectively. Comparisons with adaptive filters based on the LMS algorithm and second-order statistics are also presented in the paper.
机译:引入了一种新的基于高阶统计量的自适应干扰消除器,以减轻在非高斯干扰和与干扰高度相关的参考信号的环境中的窄带和宽带干扰。新方案使用主输入和参考输入的高阶统计量(HOS),并采用梯度类型算法来更新自适应滤波器系数。与基于二阶统计量的自适应滤波器相比,基于HOS的自适应滤波器的更新公式独立于不相关的高斯噪声,并且可以更有效地减轻干扰。的表现。与基于LMS算法的自适应滤波器相比,基于HOS的自适应滤波器对步长参数的选择要敏感得多。通过广泛的仿真证明,基于HOS的滤波器可以有效地缓解窄带和宽带干扰。本文还提出了与基于LMS算法和二阶统计量的自适应滤波器的比较。

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