Application of feature space trajectory classifier to identification of multi-aspect radar signals

Authors:
Kyung-Tae Kim
Affiliations:
School of Electrical Engineering and Computer Science, Yeungnam University, 214-1, Dae-dong, Gyeongsan-si, Gyeongsangbuk-do 712-749, Republic of Korea
Venue:
Pattern Recognition
Year:
2005

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Abstract

In this paper, a feature space trajectory (FST) classifier is applied to identify an unknown radar target. To improve the identification accuracy, we make use of information at multiple aspects of a radar target, and the FST classifier is combined with two different rules: majority vote and sum vote. In addition, two different algorithms via the simultaneous use of FST concept and line-to-line distance metric are presented to classify multi-aspect radar signals. Experimental results show that the proposed two algorithms significantly outperform the traditional FST classifier combined with majority vote and sum vote.