Autonomous time-frequency morphological feature extraction algorithm for LPI radar modulation classiflcation

被引:25
作者
Zilberman, E. R. [1 ]
Pace, P. E. [1 ]
机构
[1] Naval Postgrad Sch, Dept Elect & Comp Engn, Monterey, CA 93940 USA
来源
2006 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP 2006, PROCEEDINGS | 2006年
关键词
time-frequency analysis; CW radar; pattern classification; multi-layer perceptrons;
D O I
10.1109/ICIP.2006.312851
中图分类号
TP18 [人工智能理论];
学科分类号
081104 [模式识别与智能系统]; 0812 [计算机科学与技术]; 0835 [软件工程]; 1405 [智能科学与技术];
摘要
An autonomous (no human operator intervention) feature extraction algorithm that can be used for classification of low probability of intercept (LPI) radar modulations using time-frequency (T-F) images is presented. The approach uses erosion and a new adaptive threshold binarization algorithm embedded within a recursive dilation process to autonomously determine the modulation energy centroid (radar's carrier frequency). The modulation is then cropped from the original T-F image and the adaptive algorithm is used again to compute a binary feature vector for input into a multi-layer perceptron classification network. Classification results for five simulated radar modulations are shown to demonstrate the feature extraction approach and quantify the performance of the algorithm.
引用
收藏
页码:2321 / +
页数:2
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