Fuzzy statistical normalization CFAR detector for non-Rayleigh data

Yanwei Xu; Chaohuan Hou; Shefeng Yan; Jun Li; Chengpeng Hao

doi:10.1109/TAES.2014.130683

Fuzzy statistical normalization CFAR detector for non-Rayleigh data

Yanwei Xu
, Chaohuan Hou
, Shefeng Yan
, Jun Li
, Chengpeng Hao

CAS - Institute of Acoustics

科研成果: 期刊稿件 › 文章 › 同行评审

28 引用（Scopus）

摘要

A new constant false-alarm rate (CFAR) detector for non-Rayleigh data, based on fuzzy statistical normalization, is proposed. The proposed detector carries out the detection with two stages. The first stage of the fuzzy statistical normalization CFAR processor is background level estimation, based on fuzzy statistical normalization. The second stage is signal detection, based on the original data and the defuzzification normalized data. Performance comparisons are carried out to validate the superiority of the proposed CFAR detector.

源语言	英语
期刊论文编号	7073499
页（从-至）	383-396
页数	14
期刊	IEEE Transactions on Aerospace and Electronic Systems
卷	51
期	1
DOI	https://doi.org/10.1109/TAES.2014.130683
出版状态	已出版 - 1 1月 2015
已对外发布	是

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abstract = "A new constant false-alarm rate (CFAR) detector for non-Rayleigh data, based on fuzzy statistical normalization, is proposed. The proposed detector carries out the detection with two stages. The first stage of the fuzzy statistical normalization CFAR processor is background level estimation, based on fuzzy statistical normalization. The second stage is signal detection, based on the original data and the defuzzification normalized data. Performance comparisons are carried out to validate the superiority of the proposed CFAR detector.",

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AU - Li, Jun

AU - Hao, Chengpeng

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AB - A new constant false-alarm rate (CFAR) detector for non-Rayleigh data, based on fuzzy statistical normalization, is proposed. The proposed detector carries out the detection with two stages. The first stage of the fuzzy statistical normalization CFAR processor is background level estimation, based on fuzzy statistical normalization. The second stage is signal detection, based on the original data and the defuzzification normalized data. Performance comparisons are carried out to validate the superiority of the proposed CFAR detector.

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Fuzzy statistical normalization CFAR detector for non-Rayleigh data

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