Satellite target recognition algorithm based on BP neural networks

被引：0
|
作者：
Liu Xiankang [1 ]
Gao Meiguo [1 ]
Fu Xiongjun [1 ]
机构：
[1] Beijing Inst Technol, Inst Informat & Technol, Beijing 100081, Peoples R China
来源：
ICIEA 2007: 2ND IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS, VOLS 1-4, PROCEEDINGS | 2007年
关键词：
BP neural Networks; high resolution range profiles; central moments;
D O I：
暂无
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
For high resolution range profile (HRRP) is sensitive to pose and translation, Back-Propogation (BP) algorithm is proposed to be used to process even rank central moments of HRRP in target recognition. Wavelet denoising is used to enhance the signal noise rate (SNR) of HRRP. Then central moments are extracted from the denoised HRRP. Even rank central moments can be used as features for target recognition because they are more stable and the dimension is reduced. BP algorithm is used to process the central moments feature vector. The experimental results based on real satellites data show that the proposed method achieves good recognition performance based on its low storage and computational complexity.
引用
收藏
页码：1775 / 1778
页数：4
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