Inhomogeneity Suppression CFAR Detection Based on Statistical Modeling

被引：4
作者：
He, Xinbiao [1 ]
Xu, Yanwei [1 ]
Liu, Minggang [1 ]
Hao, Chengpeng [1 ]
机构：
[1] Univ Chinese Acad Sci, Chinese Acad Sci, Inst Acoust, Beijing 100190, Peoples R China
来源：
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS | 2023年 / 59卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Reverberation; Nonhomogeneous media; Data models; Detectors; Clutter; Image edge detection; Sonar detection; Constant false alarm rate detector (CFAR) detection; inhomogeneous background; ordered statistics; statistical modeling; ENVELOPE STATISTICS; CLUTTER;
D O I：
10.1109/TAES.2022.3198034
中图分类号：
V [航空、航天];
学科分类号：
08 ; 0825 ;
摘要：
An inhomogeneity suppression constant false alarm rate detector (IS-CFAR) based on statistical modeling is proposed for inhomogeneous sonar or radar data. First, the inhomogeneous background is modeled and classified based on ordered statistics. Then, the background power is estimated based on the different group of data according to the model of the inhomogeneous background. Finally, the IS-CFAR is designed to improve the detection performance for inhomogeneous sonar or radar data. Simulation results show that the IS-CFAR detector can suppress the background inhomogeneity and improve the CFAR detection performance under inhomogeneous background.
引用
收藏
页码：1231 / 1238
页数：8
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