The radar targets identification based on feature extraction with wavelet transformation and nearest - distance classer is studied in chapter 3 . discrete orthogonal wavelet transformation and wavelet transformation based on beylkin algorithm are applied to the samples of the targets to test their performance . the former has a better antinoise performance and the latter has a better identification rate 离散正交小波变换中提取的特征为信号的低频部分,在特征提取过程中已实现了消噪,具有较好的抗噪性能;而beylkin算法利用样本序列所有圆周移位的小波变换的高频部分,提取的信号特征虽具有移不变性,有较好的识别率,但抗噪性能较前者差。
