對(duì)稱-stable與高斯的混合噪聲中信號(hào)檢測(cè)的幾種新方法
The Innovative Signal Detection Methods in a Mixture of Symmetric -stable and Gaussian Interference
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摘要: 文章首先對(duì)現(xiàn)有-stable噪聲中信號(hào)檢測(cè)的幾種方法進(jìn)行概述、分析。在將背景噪聲拓展為對(duì)稱-stable分布噪聲和高斯噪聲的混合噪聲(一種更接近實(shí)際工程的噪聲模型)時(shí)，基于一種可逼近于對(duì)稱-stable分布的表達(dá)式，提出了幾種基于低階矩理論的信號(hào)檢測(cè)新方法。它們分別是:改進(jìn)的矩方法、局部次最優(yōu)新方法。它們有簡(jiǎn)單的表達(dá)式，容易實(shí)現(xiàn)。蒙特卡羅仿真試驗(yàn)結(jié)果表明，這幾種新方法是行之有效的，檢測(cè)性能優(yōu)于現(xiàn)有的一些方法。Abstract: After summarizing and analyzing the existing signal detection methods in a-stable noise, several innovative signal detection methods based on Fractional Low Order Moments (FLOMs) are proposed in this paper, which are the improved moment-type method and the new locally suboptimum method respectively. And these detectors are available in both the Symmetric a-stable (SaS) interference and the mixture of Gaussian and SaS interference. At the same time, Monte Carlo simulations demonstrate that all these detectors are efficient and they outperform the existing methods.
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[1] Ilow J. Dimitris Hatzinakos, Applications of the empirical characteristic function to estimation and detection problems[J].Signal Processing.1995, 65(2):199-219 -
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