Title :
An Efficient Kernel Optimization Method for High Range Resolution Profile Recognition
Author :
Chen, Bo ; Liu, Hongwei ; Bao, Zheng
Author_Institution :
Nat. Lab for Radar Signal Process., Xidian Univ., Xi´´an
Abstract :
A kernel optimization based on fusion kernel for HRRP is proposed in this paper. Based on the fusion of the 1-norm and 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 on the radar measured data the presented method is employed to the kernel optimization of KPCA and the classification performance of the extracted is evaluated via a SVM classifier. Finally, experiment results are compared and analyzed, which prove our method effective
Keywords :
Gaussian processes; optimisation; radar resolution; radar target recognition; signal classification; support vector machines; Gaussian kernels; HRRP; SVM classifier; fusion kernel optimization; high range resolution profile recognition; speckle fluctuations; Data mining; Fluctuations; Kernel; Optical scattering; Optimization methods; Radar scattering; Speckle; Support vector machine classification; Support vector machines; Target recognition; High-resolution range profile (HRRP); class separability; empirical feature space; kernel machines; kernel optimization; speckle fluctuations;
Conference_Titel :
Radar, 2006. CIE '06. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
0-7803-9582-4
Electronic_ISBN :
0-7803-9583-2
DOI :
10.1109/ICR.2006.343412
