NDLI: Autonomous Time-Frequency Morphological Feature Extraction Algorithm for LPI Radar Modulation Classification

Content Provider	IEEE Xplore Digital Library
Author	Zilberman, E.R. Pace, P.E.
Copyright Year	2006
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Naval Postgraduate Sch., Monterey, CA, USA (Zilberman, E.R.; Pace, P.E.)
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.
Starting Page	2321
Ending Page	2324
File Size	4032201
Page Count	4
File Format	PDF
ISBN	1424404800
ISSN	15224880
DOI	10.1109/ICIP.2006.312851
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-10-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Time frequency analysis Feature extraction Radar imaging Signal processing algorithms Radar detection Humans Frequency modulation Multilayer perceptrons Radar measurements Image processing Multi-layer perceptrons Time-frequency analysis CW radar Pattern classification
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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