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Technical Program
Paper Detail
| Paper: | WA-L4.2 |
| Session: | Radar Imaging |
| Time: | Wednesday, October 11, 10:00 - 10:20 |
| Presentation: |
Lecture
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| Title: |
AUTONOMOUS TIME-FREQUENCY MORPHOLOGICAL FEATURE EXTRACTION ALGORITHM FOR LPI RADAR MODULATION CLASSIFICATION |
| Authors: |
Eric Zilberman; Naval Postgraduate School | | | | | Phillip Pace; Naval Postgraduate School | | |
| Abstract: |
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. |
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