基于灰度图形状特征的低分辨雷达架次判别

Classification of Aircraft Formation for Low-Resolution Radar Based on Shape Feature of Grayscale Intensity Image

提出了一种基于回波灰度图低分辨雷达目标架次判别方法。分析了机群目标架次属性与灰度图形状结构之间的联系,对去噪后的灰度图分块提取形状特征,并采用径向基神经网络对实测四类不同架次的飞机目标数据提取的特征进行了识别,结果验证了灰度图形状特征信息的有效性,达到了较高的识别率。

This paper presents a new method based on the target＇s grayscale intensity image for classification of aircraft formation in low-resolution radar, and information about the number of aircraft formation can be got from its grayscale intensity image. After noise erased, the grayscale intensity image is divided by masses, then the shape features are extracted. The classification experiments on four kinds of aeroplane targets were conducted using these shape features as the inputs of radial basis function neural network. The results show that the vadility of feature information and the improved recognition performance.