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http://dx.doi.org/10.9766/KIMST.2016.19.3.346

Analysis on the Distribution of RF Threats Using Unsupervised Learning Techniques  

Kim, Chulpyo (School of Computer Science and Information Engineering, The Catholic University of Korea)
Noh, Sanguk (School of Computer Science and Information Engineering, The Catholic University of Korea)
Park, So Ryoung (School of Information Communication and Electronic Engineering, The Catholic University of Korea)
Publication Information
Journal of the Korea Institute of Military Science and Technology / v.19, no.3, 2016 , pp. 346-355 More about this Journal
Abstract
In this paper, we propose a method to analyze the clusters of RF threats emitting electrical signals based on collected signal variables in integrated electronic warfare environments. We first analyze the signal variables collected by an electronic warfare receiver, and construct a model based on variables showing the properties of threats. To visualize the distribution of RF threats and reversely identify them, we use k-means clustering algorithm and self-organizing map (SOM) algorithm, which are belonging to unsupervised learning techniques. Through the resulting model compiled by k-means clustering and SOM algorithms, the RF threats can be classified into one of the distribution of RF threats. In an experiment, we measure the accuracy of classification results using the algorithms, and verify the resulting model that could be used to visually recognize the distribution of RF threats.
Keywords
RF Threats; Unsupervised Learning; Self-Organizing Map; K-Means Clustering Algorithm; Integrated Electronic Warfare;
Citations & Related Records
Times Cited By KSCI : 9  (Citation Analysis)
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1 US DOD, "Electronic Warfare", Joint Publication 3-13.1, 2012.
2 D. Lee, J. Han, W. Lee, "A Kernel Density Signal Grouping Based on Radar Frequency Distribution," The Institute of Electronics Engineers of Korea - Signal Processing, Vol. 48, No. 6, pp. 124-132, November, 2011.
3 S. R. Park, H. Park, J. Ha, C. Choi, U. Jeong, S. Noh, "Designing Operational Effectiveness of Autonomously Decided Countermeasures," Journal of Korean Society for Internet Information, Vol. 13, No. 4, pp. 11-21, August, 2012.
4 J. W. Choi, S. T. Noh, S. K. Choi, "Unsupervised Classification of Landsat-8 OLI Satellite Imagery Based on Iterative Spectral Mixture Model," Journal of the Korean Society for Geospatial Information System, Vol. 22, No. 4, pp. 53-61, December, 2014.
5 S. Jun, "Spares Document Data Clustering Using Factor Score and Self Organizing Maps," Journal of The Korean Institute of Intelligent Systems, Vol. 22, No. 2, pp. 205-211, April, 2012.   DOI
6 S. Jung, S. Lim, J. Jeon, B. Kim and H. Lee, "Web Search Result Clustering using Snippets," Journal of KIISE : Databases, Vol. 39, No. 5, pp. 321-331, October, 2012.
7 K. Lee, K. Kim, M. Lee, W. Kim and J. Hong, "Post Clustering Method using Tag Hierarchy for Blog Search," The Journal of Society for e-Business Studies Vol. 16, No. 4, pp. 301-319, November, 2011.
8 J. O. Kim, "Bio-mimetic Recognition of Action Sequence using Unsupervised Learning," Journal of Korean Society for Internet Information, Vol. 15, No. 4, pp. 9-20, August, 2014.
9 K. Kim, K. Lee, "Hand Shape Detection and Recognition usin Self Organized Feature Map (SOMF) and Principal Component Analysis," The Journal of the Korea Contents Association, Vol. 13, No. 11, pp. 28-36, November, 2013.   DOI
10 H. Noh, J. Min, "A Study of Hybrid Neural Network to Improve Performance of Face Recognition," Journal of the Korea Institute of Information and Communication Enginee, Vol. 14, No. 12, pp. 2622-2627, November, 2010.   DOI
11 T. Kohonen, "The Self-Organizing Map," Neurocomputing Vol. 21, Issues 1-3, 6, 1998. 11.
12 S. Noh and U. Jeong, "Intelligent Command and Control Agent in Electronic Warfare Setting," International Journal of Intelligent Systems, Vol. 25, Issue 6, pp. 514-528, June, 2010.   DOI
13 I. H. Witten, E. Frank and M. A. Hall, "Data Mining 3/e," Morgan Kaufmann, pp. 174-175, 2010.
14 J. Vesanto, J. Himberg, E. Alhoniemi and J. Parhankangas, "Self-organizing Map in Matlab : the SOM Toolbox," Proceedings of the Matlab DSP Conference, pp. 35-40, 1999. 11.
15 J. Han, M. Kamber, J. Pei, "Data Mining : Concepts and Techniques 3/e," Morgan Kaufmann, pp. 444-454, 2011.