Study of Gaussianization Processing Based on Symmetric Alpha-stable Distribution Modeling
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Naval University of Engineering, Wuhan 430033, China
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摘要: 針對非高斯背景干擾下的弱信號檢測需求,在綜述高斯化處理與擴(kuò)展匹配濾波概念及思路的基礎(chǔ)上,該文提出了兩種基于對稱α穩(wěn)定分布建模的高斯化處理方法,構(gòu)建了相應(yīng)的擴(kuò)展匹配濾波檢測器,并對比早先建立的混合高斯分布下的高斯化處理,對其高斯化效果、對應(yīng)檢測性能、運(yùn)行速度等進(jìn)行了仿真研究。研究表明,高斯化處理可以降低背景干擾的非高斯性,從而提高后續(xù)匹配濾波的檢測性能;基于對稱α穩(wěn)定分布的高斯化處理,在保持性能的同時,具有更高的運(yùn)行效率。
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關(guān)鍵詞:
- 對稱α穩(wěn)定分布 /
- 非高斯信號處理 /
- 高斯化 /
- 擴(kuò)展匹配濾波
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. -
表 1 各EMF運(yùn)行時間統(tǒng)計比較(基于1000次檢測)
CMF EMF-Ua EMF-Ugc EMF-Ugm 均值 (ms) 0.3746 1.4699 0.4112 60.0990 方差 (ms2) 0.0014 0.0039 0.0012 43.6956 下載: 導(dǎo)出CSV
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