An Efficient Kernel Optimization Method for Radar High-Resolution Range Profile Recognition. (7th June 2007)

• Record Type: Journal Article
• Authors: Chen Chen, Bo Bo; Liu Liu, Hongwei Hongwei; Bao Bao, Zheng Zheng
• Other Names: Mecklenbräuker Mecklenbräuker Christoph Christoph Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2007(2007)
• Publication Date: 2007-06-07
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2007/49597
• Languages: English
• ISSNs: 1687-6172

Abstract

Abstract : A kernel optimization method based on fusion kernel for high-resolution range profile (HRRP) is proposed in this paper. Based on the fusion ofl 1 -norm andl 2 -norm Gaussian kernels, our method combines the different characteristics of them so that not only is the kernel function optimized but also the speckle fluctuations of HRRP are restrained. Then the proposed method is employed to optimize the kernel of kernel principle component analysis (KPCA) and the classification performance of extracted features is evaluated via support vector machines (SVMs) classifier. Finally, experimental results on the benchmark and radar-measured data sets are compared and analyzed to demonstrate the efficiency of our method.