Vector subspace detection in compound-Gaussian clutter - Part II: Performance analysis

被引：61
|
作者：
Gini, F
Farina, A
Montanari, M
机构：
[1] Univ Pisa, Dept Informat Engn, I-56126 Pisa, Italy
[2] Alenia Marconi Syst, I-00131 Rome, Italy
来源：
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS | 2002年 / 38卷 / 04期
关键词：
D O I：
10.1109/TAES.2002.1145752
中图分类号：
V [航空、航天];
学科分类号：
08 ; 0825 ;
摘要：
In this second part we deal with the problem of detecting subspace random signals against correlated non-Gaussian clutter modeled by the compound-Gaussian distribution. In the first part of the paper, we derived the optimum Neyman-Pearson (NP) detector, the generalized likelihood ratio test (GLRT), and a constant false-alarm rate (CFAR) detector; we also provided some interesting interpretations of them. In this second part, these detectors are tested against both simulated data and measured high resolution sea clutter data to investigate the dependence of their performance on the various clutter and signal parameters. Numerical examples concern a space-time adaptive processing (STAP) scenario and a ground-based surveillance radar system scenario.
引用
收藏
页码：1312 / 1323
页数：12
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