代振,,
卫红凯
海军工程大学 武汉 430033
详细信息
作者简介:王平波：男，1976年生，博士生导师，研究方向为水声信号处理、声呐作战使用等
通讯作者:代振 1663548598@qq.com
中图分类号:TN911.7计量
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被引次数:0
出版历程
收稿日期:2019-07-17
修回日期:2020-04-20
网络出版日期:2020-04-30
刊出日期:2020-09-27
Study of Gaussianization Processing Based on Symmetric Alpha-stable Distribution Modeling
Pingbo WANG,Zhen DAI,,
Hongkai WEI
Naval University of Engineering, Wuhan 430033, China
摘要
摘要:针对非高斯背景干扰下的弱信号检测需求，在综述高斯化处理与扩展匹配滤波概念及思路的基础上，该文提出了两种基于对称α稳定分布建模的高斯化处理方法，构建了相应的扩展匹配滤波检测器，并对比早先建立的混合高斯分布下的高斯化处理，对其高斯化效果、对应检测性能、运行速度等进行了仿真研究。研究表明，高斯化处理可以降低背景干扰的非高斯性，从而提高后续匹配滤波的检测性能；基于对称α稳定分布的高斯化处理，在保持性能的同时，具有更高的运行效率。
关键词:对称α稳定分布/
非高斯信号处理/
高斯化/
扩展匹配滤波
Abstract:Considering the requirement for weak signal detection in non-Gaussian background interference, after conceptions and ideas summarizing for Gaussianization processing and extended matched filter, two Gaussianizaiton filters and corresponding detections are proposed based on symmetric alpha-stable distribution modeling, comparing with those under Gaussian mixture modeling proposed earlier. All these Gaussianization filters and extended matched filters are realized in simulation. Their performances, such as Gaussianzing effect, detecting capability and running time are studies in system. Some conclusions are reached: Gaussianization can improve the detecting performance of the succeeding matched filter because of its restraining of big impulsive samples; Gaussianization filters under symmetric alpha-stable distribution modeling have higher operatiing efficiency while their peformance are similar to those under Gaussian mixture modeling.
Key words:Symmetric alpha-stable distribution/
Non-Gaussian signal processing/
Gaussianization/
Extended matched filter
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