An Intelligent Nonparametric GS Detection Algorithm Based on Adaptive Threshold Selection
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摘要: 现代雷达系统中,杂波统计特性往往无法预先确定,此时针对性较强的参量检测方法的恒虚警能力就会下降,因此非参量方法已成为一个重要的研究方向。为此,该文提出一种基于自适应阈值选择的非参量GS 检测算法(VI-GS),该检测算法结合了GS 检测算法、TGS 检测算法和GO-GS 检测算法的优点。基于仿真高斯杂波和实测雷达数据对该VI-GS 检测算法在非均匀海杂波背景下的检测性能进行分析,结果表明,在均匀杂波和非均匀杂波背景下,该算法都具有很好的鲁棒性。
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关键词:
- 非均匀背景 /
- 非参量 /
- 海杂波 /
- 广义符号(GS) /
- 削减广义符号(TGS) /
- 广义符号选大(GO-GS)
Abstract: In modern radar systems, the clutters 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.
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