ICIP 2006, Atlanta, GA
 

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Paper Detail

Paper:WA-L4.2
Session:Radar Imaging
Time:Wednesday, October 11, 10:00 - 10:20
Presentation: Lecture
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.