关键词: 合成孔径雷达, 独立分量分析, 小波, 判别熵, 自动目标识别

Abstract: Generally, single wavelet basis function and low frequency sub-band of the signal are used to perform Independent Component Analysis (ICA) in wavelet domain for Synthetic Aperture Radar (SAR) target feature extraction while high frequency sub-bands are ignored. For this defect, SAR images were decomposed utilizing multi-wavelet basis function. Then a new feature extraction method was proposed by multi-wavelet sub-band ICA according to sub-band weighted discrimination entropy criterion on the basis of the general wavelet-ICA algorithm. The SAR target recognition experiment was performed on the nearest criterion using features extracted by the new algorithm with MSTAR dataset. The experimental results show that the proposed algorithm is superior to the traditional wavelet-ICA algorithm.

Key words: Synthetic Aperture Radar (SAR), Independent Component Analysis (ICA), wavelet, discrimination entropy, Automatic Target Recognition (ATR)