Satellite Target Recognition Algorithm based on BP Neural Networks

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.

作者: Xiankang LIU Meiguo GAO Xiongjun FU

作者单位: Beijing Institute of Technology, China

会议类型: 国际会议

会议名称: 2nd IEEE Conference on Industrial Electronics and Applications(ICIEA 2007)(第二届IEEE工业电子与应用国际会议)

会议地点: 哈尔滨

会议语种:英文

在线出版日期: 2007-05-23（万方平台首次上网日期，不代表论文的发表时间）