This paper presents a new approach to radar target classification based on one-dimensional scattering centers matching.
本文提出了一种新的基于目标一维散射中心匹配的雷达目标识别方法。
Spectrum analysis is the most important branch in radar signal processing and significant of radar target classification and feature detection.
谱分析是雷达信号处理的重要组成部分，对目标分类、特征检测均有重要意义。
In classification stage, five kernel-based classifications are used and compared, and fusion methods are designed for wide-band polarimetric radar target classification.
在分类器设计环节，比较五种核非线性分类器，并根据宽带极化雷达目标散射数据的特点，使用融合分类的方法对目标进行分类。
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