A near optimum detection in alpha-stable impulsive noise

Authors:
Xutao Li; Yongquan Jiang;Miao Liu
Affiliations:
Dept. of Elec. Eng., Shantou University, Shantou, Guangdong, China;Dept. of Elec. Eng., Shantou University, Shantou, Guangdong, China;Dept. of Elec. and Computer Eng., Old Dominion University, Norfolk, VA, USA
Venue:
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Year:
2009

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Fast communication: Mixture approximation to the amplitude statistics of isotropic α-stable clutter

Signal Processing

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Abstract

Alpha stable distribution has gained much attention due to its generality to represent heavy-tailed and impulsive interference. In such non-Gaussian interference, the detection key is to evaluate the zero-memory nonlinearity (ZMNL) function of locally optimal (LO) detector. Unfortunately, there is no closed form expression for the probability density function (PDF) of alpha-stable distributions. Hereby, sub-optimum ZMNL function is adopted as an unavoidable approximation, such as classical Cauchy and Gaussian-tailed ZMNL (GZMNL). In this paper, an algebraic-tailed ZMNL (AZMNL) with a concise form is proposed. Based on such ZMNL, derived detector has near optimal performance in various impulsive noise environments. Furthermore, using Bi-parameter CGM (BCGM), a concise approximate expression for PDF of symmetric α-stable (SαS) distribution, the test threshold can be evaluated according with preset false alarm ratio easily.