基于模糊聚类的雷达目标识别

J. Jing, Wang Shouyong, Yu Lan, Zuo Delin, Yang Zhao-ming, Tang Changwen
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引用次数: 1

摘要

提出了一种利用非相干雷达窄带中频信号识别雷达目标机号的新方法。根据接收到的窄带中频回波信号,计算其自相关矩阵。特征向量为自相关矩阵的特征值,通过正交变换去除特征中不需要的信息。Karhunen-Loeve (K-L)变换是LMSE中的最优正交变换。对于平稳马尔可夫过程,如果p/spl rarr/1,则K-L变换矩阵与DCT相同,可以用FFT来完成。在k近邻分类规则的基础上,提出了一种新的模糊K-NN规则。采用上述方法取得了满意的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Radar target recognition based on fuzzy clustering
A new method of recognizing the aircraft number of a radar target from a narrowband IF signal of non-coherent radar is presented. According to the received narrowband IF echo signal, its autocorrelation matrix is computed. The feature vector is the eigenvalue of the autocorrelation matrix, and the orthogonal transformation is accomplished to remove the unnecessary information in the feature. The Karhunen-Loeve (K-L) transformation is the optimum orthogonal transformation in LMSE. For a stationary Markov process, if p/spl rarr/1, the K-L transformation matrix is the same with the DCT and can be accomplished by the FFT. Based on the K-nearest neighbor classification rule, a new fuzzy K-NN rule is presented. Satisfactory results have been obtained using the above methods.
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