Decision based non-linear filtering using interquartile range estimator for Gaussian signals

K. Buch
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引用次数: 6

Abstract

Decision based non-linear filtering is widely used for the removal of impulsive noise. Various robust statistical estimators of scale are in use for determining the threshold of the filtering process. Real-time filtering requires this estimation to be computationally efficient and realizable within the system constraints. This paper proposes the use of Interquartile range (IQR) for filtering impulsive noise from the signals possessing Gaussian distribution. The efficiency of filtering using IQR has been described through simulation for varying levels of impulsive noise. An iterative threshold for IQR based filtering has been introduced to improve the filtering efficiency. A real-time technique for computing IQR on digital hardware has been introduced. The proposed technique has applications in the areas of passive microwave radiometry, digital communications and radio astronomy.
基于决策的高斯信号四分位距离估计非线性滤波
基于决策的非线性滤波被广泛应用于脉冲噪声的去除。在确定滤波过程的阈值时,使用了各种鲁棒的尺度统计估计器。实时过滤要求这种估计在计算上是有效的,并且在系统约束下是可实现的。本文提出了利用四分位间距(IQR)从具有高斯分布的信号中滤波脉冲噪声。通过对不同程度的脉冲噪声的仿真,描述了IQR滤波的效率。为了提高滤波效率,在基于IQR的滤波中引入了迭代阈值。介绍了一种在数字硬件上实时计算IQR的技术。该技术在无源微波辐射测量、数字通信和射电天文学等领域均有应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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