FSR MARINE TARGET CLASSIFICATION WITH DATA MINING APPROACH

Dorina Kabakchieva, Hristo Kabakchiev, Vera Behar, Ivan Garvanov

Abstract

The purpose of this paper is to present the research results from a study focused on the possibilities for implementing data mining approach for classification of radar detected marine targets. The study is based on experimental data collected by researchers from Birmingham University with Bistatic Forward Scattering Radar. The data is further processed by using a CA CFAR approach for radar detection and target specific estimation, proposed by Sofia University team. Rough estimation of the target parameters in time domain in implemented, based on the hypothesis that the number of detected samples received from the target defines the target projection (length) and the energy reflected from the target. The classification models for predicting the class of the detected marine targets, achieved with selected algorithms in data mining software WEKA, for two values of the predicted variable (the marine target class), are described in the paper. The results from the evaluation of the models are compared with the results received in our previous paper, concerning classifiers achieved for predicted target variable with three values. The proposed hypothesis that the decreased number of values for the predicted variable will lead to achieving classifiers with better quality is validated.

References

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Paper Citation


in Harvard Style

Kabakchieva D., Kabakchiev H., Behar V. and Garvanov I. (2013). FSR MARINE TARGET CLASSIFICATION WITH DATA MINING APPROACH . In Proceedings of the Second International Conference on Telecommunications and Remote Sensing - Volume 1: ICTRS, ISBN 978-989-8565-57-0, pages 145-152. DOI: 10.5220/0004786501450152


in Bibtex Style

@conference{ictrs13,
author={Dorina Kabakchieva and Hristo Kabakchiev and Vera Behar and Ivan Garvanov},
title={FSR MARINE TARGET CLASSIFICATION WITH DATA MINING APPROACH},
booktitle={Proceedings of the Second International Conference on Telecommunications and Remote Sensing - Volume 1: ICTRS,},
year={2013},
pages={145-152},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004786501450152},
isbn={978-989-8565-57-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Telecommunications and Remote Sensing - Volume 1: ICTRS,
TI - FSR MARINE TARGET CLASSIFICATION WITH DATA MINING APPROACH
SN - 978-989-8565-57-0
AU - Kabakchieva D.
AU - Kabakchiev H.
AU - Behar V.
AU - Garvanov I.
PY - 2013
SP - 145
EP - 152
DO - 10.5220/0004786501450152