Open AccessAn Intelligent Nonparametric GS Detection Algorithm Based on Adaptive Threshold Selection
Author(s) -
Lin Zhang,
Zhong-Qiu Zhao,
Jian Guan,
Yansong He
Publication year - 2012
Publication title -
leida xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.301
H-Index - 13
ISSN - 2095-283X
DOI - 10.3724/sp.j.1300.2012.20084
Subject(s) - nonparametric statistics , computer science , selection (genetic algorithm) , algorithm , artificial intelligence , pattern recognition (psychology) , mathematics , statistics
In modern radar systems, the clutter’s statistic characters are unknown. With this clutter, the capability of CFAR of parametric detection algorithms will decline. So nonparametric detection algorithms become very important. An intelligent nonparametric Generalized Sign (GS) detection algorithm Variability Index-Generalized Sign (VI-GS) based on adaptive threshold selection is proposed. The VI-GS detection algorithm comploys a composite approach based on the GS detection algorithm, the Trimmed GS detection algorithm (TGS) and the Greatest Of GS detection algorithm (GO-GS). The performance of this detection algorithm in the nonhomogenous clutter background is analyzed respectively based on simulated Gaussian distributed clutter and real radar data. These results show that it performs robustly in the homogeneous background as well as the nonhomogeneous background