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基于多分类器融合的雷达高分辨距离像目标识别与拒判新方法

DOI: 10.3724/SP.J.1004.2014.00348, PP. 348-356

Keywords: 雷达自动目标识别,多分类器融合,库外样本拒判,最优工作点选择

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Abstract:

?由于雷达自动目标识别(Radarautomatictargetrecognition,RATR)中库外目标的存在,评价系统性能时应综合考虑其识别性能和拒判性能.由此本文构造了一种将分类器的输出通过最近邻分类器(Nearestneighbor,NN)进行拒判和识别的“分类器——最近邻”系统,并在拒判和识别两个阶段分别采用多分类器融合技术以提高RATR系统的拒判和识别综合性能.此外,文中定义了一种代价函数以衡量系统综合性能并为系统拒判工作点的选取提供依据.进而,采用局部法和全局法两种算法确定拒判器的工作点.实测数据实验结果验证了本文方法的有效性,两种工作点选取算法均能够显著提高识别系统的综合性能.

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